{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compare RAPL to CodeCarbon estimation with CPU load"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_df(csv):\n",
    "    df = pd.read_csv(csv)\n",
    "    df = df.sort_values(by='cpu_load')\n",
    "    return df\n",
    "\n",
    "def display_df(df):\n",
    "    return df[\"cores_used\tcpu_load\ttemperature\tcpu_freq\trapl_power\testimated_power\ttapo_power\ttapo_energy\".split(\"\\t\")]\n",
    "\n",
    "def plot(df, with_tapo=False):\n",
    "    # Plot the power in Y and the CPU load in X\n",
    "    if with_tapo:\n",
    "        return df.plot(x='cpu_load', y=['tapo_power', 'rapl_power', 'estimated_power'], kind='line', title='CPU Load vs Power Consumption')\n",
    "    else:\n",
    "        return df.plot(x='cpu_load', y=['rapl_power', 'estimated_power'], kind='line', title='CPU Load vs Power Consumption')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dual Intel Xeon E5-2620 v3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The machine we use had 2 CPU Intel(R) Xeon(R) CPU E5-2620 v3 @ 2.40GHz and 192 GB of RAM.\n",
    "\n",
    "The TDP of the CPU is 85W in CodeCarbon database, that use https://www.intel.fr/content/www/fr/fr/products/sku/83352/intel-xeon-processor-e52620-v3-15m-cache-2-40-ghz/specifications.html as a source.\n",
    "\n",
    "It means that 2 CPU at 100% load could consume 170W.\n",
    "\n",
    "So CodeCarbon will use 170W as the maximum and estimate the power from the CPU load.\n",
    "\n",
    "But what we see is that the power consumption reported by RAPL is much lower than 170W.\n",
    "\n",
    "When using stress-ng to stress the CPU, we see:\n",
    "    \n",
    "```bash\n",
    "stress-ng: info:  [8883]  pkg-0                  59.07 W\n",
    "stress-ng: info:  [8883]  pkg-1                  63.03 W\n",
    "```\n",
    "\n",
    "So the maximum power consumption is around 120W. That mean the something is limiting the chip at 70% of his TDP.\n",
    "\n",
    "I, the documentation of the CPU, we can see that there is a Turbo Boost frequency of 3.20 GHz and a base frequency of 2.40 GHz. So it is possible that the measured TDP is limited by the frequency, as in our log we see that we are at a maximum of 2.4 GHz. Maybe it is a indicator to get the real max power of the CPU ?\n",
    "\n",
    "\n",
    "\n",
    "We see below that RAPL report from CodeCarbon give the same results as the tool Stress-ng when we use all core and stress them at a given percentage of the load.\n",
    "\n",
    "But when using stress-ng to use only some core we sam a lower power consumption reported by RAPL. => This is not expected. I ran the experiment a second time and the results were the same. Our stress system does not seem to be able to really stress the CPU despite the reported load."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cores_used</th>\n",
       "      <th>cpu_load</th>\n",
       "      <th>temperature</th>\n",
       "      <th>cpu_freq</th>\n",
       "      <th>rapl_power</th>\n",
       "      <th>estimated_power</th>\n",
       "      <th>tapo_power</th>\n",
       "      <th>tapo_energy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32.928571</td>\n",
       "      <td>1666.677792</td>\n",
       "      <td>0.513387</td>\n",
       "      <td>0.137097</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>24</td>\n",
       "      <td>10.0</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>1395.867083</td>\n",
       "      <td>16.393232</td>\n",
       "      <td>16.703871</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24</td>\n",
       "      <td>20.0</td>\n",
       "      <td>35.214286</td>\n",
       "      <td>1200.067875</td>\n",
       "      <td>30.981250</td>\n",
       "      <td>33.150000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24</td>\n",
       "      <td>30.0</td>\n",
       "      <td>36.428571</td>\n",
       "      <td>1200.092417</td>\n",
       "      <td>38.410990</td>\n",
       "      <td>49.546774</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24</td>\n",
       "      <td>40.5</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>1359.369958</td>\n",
       "      <td>45.282212</td>\n",
       "      <td>65.927097</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>24</td>\n",
       "      <td>50.2</td>\n",
       "      <td>40.071429</td>\n",
       "      <td>1675.181583</td>\n",
       "      <td>62.157340</td>\n",
       "      <td>82.307419</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>24</td>\n",
       "      <td>60.0</td>\n",
       "      <td>42.428571</td>\n",
       "      <td>2081.623833</td>\n",
       "      <td>61.948856</td>\n",
       "      <td>98.649355</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>24</td>\n",
       "      <td>69.9</td>\n",
       "      <td>47.428571</td>\n",
       "      <td>2600.282250</td>\n",
       "      <td>76.923346</td>\n",
       "      <td>114.920000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>24</td>\n",
       "      <td>80.8</td>\n",
       "      <td>49.714286</td>\n",
       "      <td>2606.114833</td>\n",
       "      <td>111.884608</td>\n",
       "      <td>131.256452</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>24</td>\n",
       "      <td>89.7</td>\n",
       "      <td>51.642857</td>\n",
       "      <td>2566.944875</td>\n",
       "      <td>115.807523</td>\n",
       "      <td>147.631290</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>24</td>\n",
       "      <td>99.6</td>\n",
       "      <td>51.214286</td>\n",
       "      <td>2400.266000</td>\n",
       "      <td>117.017473</td>\n",
       "      <td>163.770323</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cores_used  cpu_load  temperature     cpu_freq  rapl_power  \\\n",
       "0           24       0.0    32.928571  1666.677792    0.513387   \n",
       "1           24      10.0    34.000000  1395.867083   16.393232   \n",
       "2           24      20.0    35.214286  1200.067875   30.981250   \n",
       "3           24      30.0    36.428571  1200.092417   38.410990   \n",
       "4           24      40.5    39.000000  1359.369958   45.282212   \n",
       "5           24      50.2    40.071429  1675.181583   62.157340   \n",
       "6           24      60.0    42.428571  2081.623833   61.948856   \n",
       "7           24      69.9    47.428571  2600.282250   76.923346   \n",
       "8           24      80.8    49.714286  2606.114833  111.884608   \n",
       "9           24      89.7    51.642857  2566.944875  115.807523   \n",
       "10          24      99.6    51.214286  2400.266000  117.017473   \n",
       "\n",
       "    estimated_power  tapo_power  tapo_energy  \n",
       "0          0.137097           0            0  \n",
       "1         16.703871           0            0  \n",
       "2         33.150000           0            0  \n",
       "3         49.546774           0            0  \n",
       "4         65.927097           0            0  \n",
       "5         82.307419           0            0  \n",
       "6         98.649355           0            0  \n",
       "7        114.920000           0            0  \n",
       "8        131.256452           0            0  \n",
       "9        147.631290           0            0  \n",
       "10       163.770323           0            0  "
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv = '../codecarbon/data/hardware/cpu_load_profiling/E5-2620/compare_cpu_load_and_RAPL-all_cores-Intel(R)_Xeon(R)_CPU_E5-2620_v3_@_2.40GHz-2025-01-14.csv'\n",
    "df_all_cores = get_df(csv)\n",
    "display_df(df_all_cores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plot(df_all_cores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cores_used</th>\n",
       "      <th>cpu_load</th>\n",
       "      <th>temperature</th>\n",
       "      <th>cpu_freq</th>\n",
       "      <th>rapl_power</th>\n",
       "      <th>estimated_power</th>\n",
       "      <th>tapo_power</th>\n",
       "      <th>tapo_energy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.142857</td>\n",
       "      <td>1479.197167</td>\n",
       "      <td>0.506529</td>\n",
       "      <td>0.104194</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>8.7</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1316.737583</td>\n",
       "      <td>16.312251</td>\n",
       "      <td>13.852258</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>17.0</td>\n",
       "      <td>40.142857</td>\n",
       "      <td>1212.538958</td>\n",
       "      <td>34.766380</td>\n",
       "      <td>27.671613</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>29.0</td>\n",
       "      <td>41.214286</td>\n",
       "      <td>1361.311333</td>\n",
       "      <td>39.833439</td>\n",
       "      <td>48.153871</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9</td>\n",
       "      <td>37.9</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1200.055833</td>\n",
       "      <td>49.544123</td>\n",
       "      <td>61.923871</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12</td>\n",
       "      <td>50.0</td>\n",
       "      <td>42.214286</td>\n",
       "      <td>1254.206958</td>\n",
       "      <td>50.489318</td>\n",
       "      <td>82.455484</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>14</td>\n",
       "      <td>58.7</td>\n",
       "      <td>43.642857</td>\n",
       "      <td>1400.101208</td>\n",
       "      <td>67.126244</td>\n",
       "      <td>96.154194</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>16</td>\n",
       "      <td>66.7</td>\n",
       "      <td>44.642857</td>\n",
       "      <td>1458.430917</td>\n",
       "      <td>71.548678</td>\n",
       "      <td>109.874839</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>19</td>\n",
       "      <td>79.2</td>\n",
       "      <td>45.928571</td>\n",
       "      <td>1721.068375</td>\n",
       "      <td>72.030833</td>\n",
       "      <td>130.433871</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>21</td>\n",
       "      <td>87.5</td>\n",
       "      <td>46.214286</td>\n",
       "      <td>1712.701917</td>\n",
       "      <td>75.746365</td>\n",
       "      <td>144.105161</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>24</td>\n",
       "      <td>100.0</td>\n",
       "      <td>48.071429</td>\n",
       "      <td>2250.244458</td>\n",
       "      <td>79.605676</td>\n",
       "      <td>164.373548</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cores_used  cpu_load  temperature     cpu_freq  rapl_power  \\\n",
       "0            0       0.0    42.142857  1479.197167    0.506529   \n",
       "1            2       8.7    41.000000  1316.737583   16.312251   \n",
       "2            4      17.0    40.142857  1212.538958   34.766380   \n",
       "3            7      29.0    41.214286  1361.311333   39.833439   \n",
       "4            9      37.9    41.000000  1200.055833   49.544123   \n",
       "5           12      50.0    42.214286  1254.206958   50.489318   \n",
       "6           14      58.7    43.642857  1400.101208   67.126244   \n",
       "7           16      66.7    44.642857  1458.430917   71.548678   \n",
       "8           19      79.2    45.928571  1721.068375   72.030833   \n",
       "9           21      87.5    46.214286  1712.701917   75.746365   \n",
       "10          24     100.0    48.071429  2250.244458   79.605676   \n",
       "\n",
       "    estimated_power  tapo_power  tapo_energy  \n",
       "0          0.104194           0            0  \n",
       "1         13.852258           0            0  \n",
       "2         27.671613           0            0  \n",
       "3         48.153871           0            0  \n",
       "4         61.923871           0            0  \n",
       "5         82.455484           0            0  \n",
       "6         96.154194           0            0  \n",
       "7        109.874839           0            0  \n",
       "8        130.433871           0            0  \n",
       "9        144.105161           0            0  \n",
       "10       164.373548           0            0  "
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv = '../codecarbon/data/hardware/cpu_load_profiling/E5-2620/compare_cpu_load_and_RAPL-some_cores-Intel(R)_Xeon(R)_CPU_E5-2620_v3_@_2.40GHz-2025-01-14.csv'\n",
    "df_some_cores = get_df(csv)\n",
    "display_df(df_some_cores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plot(df_some_cores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## AMD EPYC 8024P 8-Core Processor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The command `stress-ng --cpu 0 --cpu-method matrixprod --metrics-brief --rapl --perf -t 60s` give :\n",
    "\n",
    "```bash\n",
    "stress-ng: info:  [6071]  core                    1.89 W\n",
    "stress-ng: info:  [6071]  pkg-0                  53.45 W\n",
    "```\n",
    "\n",
    "Here we saw that `core` is not used in the same way on AMD CPU than on Intel:\n",
    "\n",
    "- Intel put all the core consumption in `core` and the `package` include `core`.\n",
    "- AMD `core` have very low power, so we don't know if it is included in the `package` or not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "# !scp ubuntu@195.154.100.237:/home/ubuntu/codecarbon/*.csv ../codecarbon/data/hardware/cpu_load_profiling/AMD_EPYC_8024P_8C/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cores_used</th>\n",
       "      <th>cpu_load</th>\n",
       "      <th>temperature</th>\n",
       "      <th>cpu_freq</th>\n",
       "      <th>rapl_power</th>\n",
       "      <th>estimated_power</th>\n",
       "      <th>tapo_power</th>\n",
       "      <th>tapo_energy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0</td>\n",
       "      <td>1588.803813</td>\n",
       "      <td>0.589091</td>\n",
       "      <td>0.528387</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1499.249313</td>\n",
       "      <td>18.614618</td>\n",
       "      <td>9.351290</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>16</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1710.875750</td>\n",
       "      <td>29.500629</td>\n",
       "      <td>18.087097</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2275.445813</td>\n",
       "      <td>38.665937</td>\n",
       "      <td>26.628387</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>16</td>\n",
       "      <td>40.3</td>\n",
       "      <td>0</td>\n",
       "      <td>2005.789937</td>\n",
       "      <td>41.753242</td>\n",
       "      <td>35.129032</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>16</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2995.390687</td>\n",
       "      <td>43.218847</td>\n",
       "      <td>43.960645</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>16</td>\n",
       "      <td>64.6</td>\n",
       "      <td>0</td>\n",
       "      <td>2995.056562</td>\n",
       "      <td>47.602355</td>\n",
       "      <td>52.647097</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>16</td>\n",
       "      <td>70.2</td>\n",
       "      <td>0</td>\n",
       "      <td>2995.415937</td>\n",
       "      <td>48.713748</td>\n",
       "      <td>61.330645</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>16</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2995.051500</td>\n",
       "      <td>49.294313</td>\n",
       "      <td>69.781935</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>16</td>\n",
       "      <td>89.4</td>\n",
       "      <td>0</td>\n",
       "      <td>2995.331437</td>\n",
       "      <td>50.717957</td>\n",
       "      <td>78.465484</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>16</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2960.064250</td>\n",
       "      <td>46.079992</td>\n",
       "      <td>86.626452</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cores_used  cpu_load  temperature     cpu_freq  rapl_power  \\\n",
       "0           16       0.6            0  1588.803813    0.589091   \n",
       "1           16      10.0            0  1499.249313   18.614618   \n",
       "2           16      20.0            0  1710.875750   29.500629   \n",
       "3           16      30.0            0  2275.445813   38.665937   \n",
       "4           16      40.3            0  2005.789937   41.753242   \n",
       "5           16      50.0            0  2995.390687   43.218847   \n",
       "6           16      64.6            0  2995.056562   47.602355   \n",
       "7           16      70.2            0  2995.415937   48.713748   \n",
       "8           16      80.0            0  2995.051500   49.294313   \n",
       "9           16      89.4            0  2995.331437   50.717957   \n",
       "10          16     100.0            0  2960.064250   46.079992   \n",
       "\n",
       "    estimated_power  tapo_power  tapo_energy  \n",
       "0          0.528387           0            0  \n",
       "1          9.351290           0            0  \n",
       "2         18.087097           0            0  \n",
       "3         26.628387           0            0  \n",
       "4         35.129032           0            0  \n",
       "5         43.960645           0            0  \n",
       "6         52.647097           0            0  \n",
       "7         61.330645           0            0  \n",
       "8         69.781935           0            0  \n",
       "9         78.465484           0            0  \n",
       "10        86.626452           0            0  "
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv = '../codecarbon/data/hardware/cpu_load_profiling/AMD_EPYC_8024P_8C/compare_cpu_load_and_RAPL-all_cores-AMD_EPYC_8024P_8-Core_Processor-2025-01-14.csv'\n",
    "df_all_cores = get_df(csv)\n",
    "display_df(df_all_cores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plot(df_all_cores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cores_used</th>\n",
       "      <th>cpu_load</th>\n",
       "      <th>temperature</th>\n",
       "      <th>cpu_freq</th>\n",
       "      <th>rapl_power</th>\n",
       "      <th>estimated_power</th>\n",
       "      <th>tapo_power</th>\n",
       "      <th>tapo_energy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1573.689562</td>\n",
       "      <td>0.570342</td>\n",
       "      <td>0.400645</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>6.8</td>\n",
       "      <td>0</td>\n",
       "      <td>1674.014938</td>\n",
       "      <td>18.321380</td>\n",
       "      <td>6.143226</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>18.6</td>\n",
       "      <td>0</td>\n",
       "      <td>1875.329125</td>\n",
       "      <td>37.675483</td>\n",
       "      <td>16.798065</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>24.8</td>\n",
       "      <td>0</td>\n",
       "      <td>1917.428375</td>\n",
       "      <td>41.647884</td>\n",
       "      <td>22.357742</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>37.3</td>\n",
       "      <td>0</td>\n",
       "      <td>2390.904875</td>\n",
       "      <td>43.577488</td>\n",
       "      <td>33.128710</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8</td>\n",
       "      <td>50.3</td>\n",
       "      <td>0</td>\n",
       "      <td>2577.975125</td>\n",
       "      <td>47.224847</td>\n",
       "      <td>43.899677</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>9</td>\n",
       "      <td>56.2</td>\n",
       "      <td>0</td>\n",
       "      <td>2552.963062</td>\n",
       "      <td>49.348596</td>\n",
       "      <td>49.531935</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>11</td>\n",
       "      <td>71.6</td>\n",
       "      <td>0</td>\n",
       "      <td>2786.423500</td>\n",
       "      <td>49.929497</td>\n",
       "      <td>60.294194</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>12</td>\n",
       "      <td>78.1</td>\n",
       "      <td>0</td>\n",
       "      <td>2864.899562</td>\n",
       "      <td>51.111553</td>\n",
       "      <td>65.874194</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>14</td>\n",
       "      <td>87.5</td>\n",
       "      <td>0</td>\n",
       "      <td>2994.788312</td>\n",
       "      <td>45.597339</td>\n",
       "      <td>76.746774</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>16</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2953.205188</td>\n",
       "      <td>46.506666</td>\n",
       "      <td>87.015484</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cores_used  cpu_load  temperature     cpu_freq  rapl_power  \\\n",
       "0            0       0.0            0  1573.689562    0.570342   \n",
       "1            1       6.8            0  1674.014938   18.321380   \n",
       "2            3      18.6            0  1875.329125   37.675483   \n",
       "3            4      24.8            0  1917.428375   41.647884   \n",
       "4            6      37.3            0  2390.904875   43.577488   \n",
       "5            8      50.3            0  2577.975125   47.224847   \n",
       "6            9      56.2            0  2552.963062   49.348596   \n",
       "7           11      71.6            0  2786.423500   49.929497   \n",
       "8           12      78.1            0  2864.899562   51.111553   \n",
       "9           14      87.5            0  2994.788312   45.597339   \n",
       "10          16     100.0            0  2953.205188   46.506666   \n",
       "\n",
       "    estimated_power  tapo_power  tapo_energy  \n",
       "0          0.400645           0            0  \n",
       "1          6.143226           0            0  \n",
       "2         16.798065           0            0  \n",
       "3         22.357742           0            0  \n",
       "4         33.128710           0            0  \n",
       "5         43.899677           0            0  \n",
       "6         49.531935           0            0  \n",
       "7         60.294194           0            0  \n",
       "8         65.874194           0            0  \n",
       "9         76.746774           0            0  \n",
       "10        87.015484           0            0  "
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv = '../codecarbon/data/hardware/cpu_load_profiling/AMD_EPYC_8024P_8C/compare_cpu_load_and_RAPL-some_cores-AMD_EPYC_8024P_8-Core_Processor-2025-01-14.csv'\n",
    "df_some_cores = get_df(csv)\n",
    "display_df(df_some_cores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plot(df_some_cores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## AMD Ryzen Threadripper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cores_used</th>\n",
       "      <th>cpu_load</th>\n",
       "      <th>temperature</th>\n",
       "      <th>cpu_freq</th>\n",
       "      <th>rapl_power</th>\n",
       "      <th>estimated_power</th>\n",
       "      <th>tapo_power</th>\n",
       "      <th>tapo_energy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>32</td>\n",
       "      <td>2.8</td>\n",
       "      <td>34.0</td>\n",
       "      <td>2332.872375</td>\n",
       "      <td>1.376694</td>\n",
       "      <td>2.685484</td>\n",
       "      <td>115</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>32</td>\n",
       "      <td>13.9</td>\n",
       "      <td>39.0</td>\n",
       "      <td>2398.106938</td>\n",
       "      <td>43.301572</td>\n",
       "      <td>18.416323</td>\n",
       "      <td>147</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>32</td>\n",
       "      <td>23.2</td>\n",
       "      <td>49.0</td>\n",
       "      <td>2525.592844</td>\n",
       "      <td>62.548276</td>\n",
       "      <td>51.952645</td>\n",
       "      <td>198</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>32</td>\n",
       "      <td>36.4</td>\n",
       "      <td>46.0</td>\n",
       "      <td>2797.558437</td>\n",
       "      <td>79.171048</td>\n",
       "      <td>82.757979</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>32</td>\n",
       "      <td>44.8</td>\n",
       "      <td>51.0</td>\n",
       "      <td>2821.125656</td>\n",
       "      <td>106.327887</td>\n",
       "      <td>121.690031</td>\n",
       "      <td>257</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>32</td>\n",
       "      <td>53.1</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2987.127656</td>\n",
       "      <td>128.126800</td>\n",
       "      <td>150.751423</td>\n",
       "      <td>219</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>32</td>\n",
       "      <td>66.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>3690.573406</td>\n",
       "      <td>144.148902</td>\n",
       "      <td>160.822844</td>\n",
       "      <td>285</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>32</td>\n",
       "      <td>72.1</td>\n",
       "      <td>57.0</td>\n",
       "      <td>3576.535531</td>\n",
       "      <td>172.434844</td>\n",
       "      <td>166.203430</td>\n",
       "      <td>278</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>32</td>\n",
       "      <td>83.1</td>\n",
       "      <td>56.0</td>\n",
       "      <td>3418.626969</td>\n",
       "      <td>170.324487</td>\n",
       "      <td>169.046276</td>\n",
       "      <td>279</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>32</td>\n",
       "      <td>91.7</td>\n",
       "      <td>56.0</td>\n",
       "      <td>3357.159875</td>\n",
       "      <td>169.175124</td>\n",
       "      <td>170.991107</td>\n",
       "      <td>277</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>32</td>\n",
       "      <td>99.7</td>\n",
       "      <td>56.0</td>\n",
       "      <td>3323.423719</td>\n",
       "      <td>166.891447</td>\n",
       "      <td>172.011089</td>\n",
       "      <td>278</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cores_used  cpu_load  temperature     cpu_freq  rapl_power  \\\n",
       "0           32       2.8         34.0  2332.872375    1.376694   \n",
       "1           32      13.9         39.0  2398.106938   43.301572   \n",
       "2           32      23.2         49.0  2525.592844   62.548276   \n",
       "3           32      36.4         46.0  2797.558437   79.171048   \n",
       "4           32      44.8         51.0  2821.125656  106.327887   \n",
       "5           32      53.1         52.0  2987.127656  128.126800   \n",
       "6           32      66.0         56.0  3690.573406  144.148902   \n",
       "7           32      72.1         57.0  3576.535531  172.434844   \n",
       "8           32      83.1         56.0  3418.626969  170.324487   \n",
       "9           32      91.7         56.0  3357.159875  169.175124   \n",
       "10          32      99.7         56.0  3323.423719  166.891447   \n",
       "\n",
       "    estimated_power  tapo_power  tapo_energy  \n",
       "0          2.685484         115            0  \n",
       "1         18.416323         147            2  \n",
       "2         51.952645         198            1  \n",
       "3         82.757979         226            2  \n",
       "4        121.690031         257            2  \n",
       "5        150.751423         219            2  \n",
       "6        160.822844         285            2  \n",
       "7        166.203430         278            3  \n",
       "8        169.046276         279            2  \n",
       "9        170.991107         277            2  \n",
       "10       172.011089         278            3  "
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv = '../codecarbon/data/hardware/cpu_load_profiling/AMD_Threadripper/compare_cpu_load_and_RAPL-all_cores-AMD_Ryzen_Threadripper_1950X_16-Core_Processor-2025-01-14.csv'\n",
    "df_all_cores = get_df(csv)\n",
    "display_df(df_all_cores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plot(df_all_cores, with_tapo=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cores_used</th>\n",
       "      <th>cpu_load</th>\n",
       "      <th>temperature</th>\n",
       "      <th>cpu_freq</th>\n",
       "      <th>rapl_power</th>\n",
       "      <th>estimated_power</th>\n",
       "      <th>tapo_power</th>\n",
       "      <th>tapo_energy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>2404.504125</td>\n",
       "      <td>1.431431</td>\n",
       "      <td>2.540323</td>\n",
       "      <td>161</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>12.2</td>\n",
       "      <td>53.0</td>\n",
       "      <td>2470.488313</td>\n",
       "      <td>45.384826</td>\n",
       "      <td>15.636774</td>\n",
       "      <td>159</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>22.9</td>\n",
       "      <td>57.0</td>\n",
       "      <td>2782.765875</td>\n",
       "      <td>76.236165</td>\n",
       "      <td>45.202645</td>\n",
       "      <td>178</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9</td>\n",
       "      <td>32.2</td>\n",
       "      <td>53.0</td>\n",
       "      <td>2985.716781</td>\n",
       "      <td>93.332591</td>\n",
       "      <td>79.437879</td>\n",
       "      <td>266</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12</td>\n",
       "      <td>41.4</td>\n",
       "      <td>56.0</td>\n",
       "      <td>3206.834594</td>\n",
       "      <td>123.021109</td>\n",
       "      <td>106.222332</td>\n",
       "      <td>278</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>16</td>\n",
       "      <td>52.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>3497.221406</td>\n",
       "      <td>147.402916</td>\n",
       "      <td>151.955486</td>\n",
       "      <td>278</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>19</td>\n",
       "      <td>64.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>3411.514031</td>\n",
       "      <td>174.783770</td>\n",
       "      <td>161.294986</td>\n",
       "      <td>279</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>22</td>\n",
       "      <td>73.1</td>\n",
       "      <td>60.0</td>\n",
       "      <td>3552.373969</td>\n",
       "      <td>173.309731</td>\n",
       "      <td>165.967674</td>\n",
       "      <td>324</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>25</td>\n",
       "      <td>80.1</td>\n",
       "      <td>60.0</td>\n",
       "      <td>3314.471656</td>\n",
       "      <td>169.427395</td>\n",
       "      <td>169.160416</td>\n",
       "      <td>326</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>28</td>\n",
       "      <td>92.5</td>\n",
       "      <td>59.0</td>\n",
       "      <td>3611.685188</td>\n",
       "      <td>167.419962</td>\n",
       "      <td>170.802339</td>\n",
       "      <td>280</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>32</td>\n",
       "      <td>100.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>3399.256594</td>\n",
       "      <td>166.033463</td>\n",
       "      <td>172.117387</td>\n",
       "      <td>290</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cores_used  cpu_load  temperature     cpu_freq  rapl_power  \\\n",
       "0            0       5.0         44.0  2404.504125    1.431431   \n",
       "1            3      12.2         53.0  2470.488313   45.384826   \n",
       "2            6      22.9         57.0  2782.765875   76.236165   \n",
       "3            9      32.2         53.0  2985.716781   93.332591   \n",
       "4           12      41.4         56.0  3206.834594  123.021109   \n",
       "5           16      52.0         59.0  3497.221406  147.402916   \n",
       "6           19      64.0         61.0  3411.514031  174.783770   \n",
       "7           22      73.1         60.0  3552.373969  173.309731   \n",
       "8           25      80.1         60.0  3314.471656  169.427395   \n",
       "9           28      92.5         59.0  3611.685188  167.419962   \n",
       "10          32     100.0         58.0  3399.256594  166.033463   \n",
       "\n",
       "    estimated_power  tapo_power  tapo_energy  \n",
       "0          2.540323         161            2  \n",
       "1         15.636774         159            1  \n",
       "2         45.202645         178            2  \n",
       "3         79.437879         266            2  \n",
       "4        106.222332         278            2  \n",
       "5        151.955486         278            2  \n",
       "6        161.294986         279            3  \n",
       "7        165.967674         324            2  \n",
       "8        169.160416         326            3  \n",
       "9        170.802339         280            3  \n",
       "10       172.117387         290            2  "
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv = '../codecarbon/data/hardware/cpu_load_profiling/AMD_Threadripper/compare_cpu_load_and_RAPL-some_cores-AMD_Ryzen_Threadripper_1950X_16-Core_Processor-2025-01-14.csv'\n",
    "df_some_cores = get_df(csv)\n",
    "display_df(df_some_cores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAigAAAHHCAYAAACV96NPAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQAAiblJREFUeJzs3Xd8Tfcfx/HXvTd7y5KEIHbsESO2UqqoWbRqtEapqFG0OpS2flqqqi2lkw6tUaNWWytm7E0EMRIjg8heN/ee3x9XLtdMSHIzPs/H4z6Ssz/3JNx3vud7vkelKIqCEEIIIUQhojZ3AUIIIYQQ95KAIoQQQohCRwKKEEIIIQodCShCCCGEKHQkoAghhBCi0JGAIoQQQohCRwKKEEIIIQodCShCCCGEKHQkoAghhBCi0JGAIkQhdunSJVQqFYsWLTJ3KULkmPzeirwgAUWYVXh4OK+//joVK1bExsYGJycnmjdvzty5c0lLSzOuV6FCBVQqlfHl6elJy5YtWbVqlcn+KlSoQJcuXR54rIMHD+boP83g4GBUKhUrVqx46vdXXCxatMjk/NvY2FC1alWCgoKIjo42d3l5ZtWqVXTq1Al3d3esrKzw8fGhT58+bN261dylFUpLlizhyy+/NHcZopiyMHcBouRav349L774ItbW1gwcOJBatWqRmZnJrl27mDhxIqdOneK7774zrl+vXj3eeustAK5du8bChQvp2bMn3377LSNGjDDX2yhRPvroI/z8/EhPT2fXrl18++23bNiwgZMnT2JnZ2fu8p6Yoii89tprLFq0iPr16zN+/Hi8vLy4fv06q1atol27duzevZtmzZqZu9RCZcmSJZw8eZKxY8eazC9fvjxpaWlYWlqapzBRLEhAEWZx8eJF+vXrR/ny5dm6dSve3t7GZaNGjeL8+fOsX7/eZJsyZcrwyiuvGKcHDhxI5cqVmTNnjgSUAtKpUycCAgIAGDp0KG5ubnzxxResWbOGl156yczVPZxeryczMxMbG5sHLp89ezaLFi1i7NixfPHFF6hUKuOy9957j19//RULC/nvMqeyW9mEeBpyiUeYxcyZM0lOTubHH380CSfZKleuzJgxYx65Dy8vL/z9/bl48WJ+lflIFy5c4MUXX8TV1RU7OzuaNm16X6jKzMxkypQpNGzYEGdnZ+zt7WnZsiXbtm27b3/x8fEMHjwYZ2dnXFxcGDRoEPHx8Y+tI/vS1eLFi+9b9u+//6JSqVi3bh0ASUlJjB07lgoVKmBtbY2npyfPPvsshw8ffqJz8MwzzwAYfwZZWVl8/PHHVKpUCWtraypUqMC7775LRkaGcZvx48fj5ubG3Q9SHz16NCqViq+++so4Lzo6GpVKxbfffmucl5GRwYcffkjlypWxtrbG19eXSZMmmewfDB+QQUFB/P7779SsWRNra2v++eefB76HtLQ0ZsyYQfXq1fn8889Nwkm2AQMG0LhxY+N0Tn722ZcKly1bxvTp0ylbtiw2Nja0a9eO8+fPm6x77tw5evXqhZeXFzY2NpQtW5Z+/fqRkJAAPLpPh0qlYurUqcbpqVOnolKpOHv2LK+88grOzs54eHjwwQcfoCgKkZGRdOvWDScnJ7y8vJg9e/YD6166dCnvvvsuXl5e2Nvb88ILLxAZGWlcr02bNqxfv57Lly8bL/1VqFDhkfVu3bqVli1bYm9vj4uLC926dSM0NNRknez6z58/z+DBg3FxccHZ2ZlXX32V1NTU+96/KL7kTwJhFmvXrqVixYpP1WSu1WqJjIzEzc0tDyvLmejoaJo1a0Zqaipvvvkmbm5uLF68mBdeeIEVK1bQo0cPABITE/nhhx946aWXGDZsGElJSfz444907NiR/fv3U69ePcBwiaFbt27s2rWLESNG4O/vz6pVqxg0aNBjawkICKBixYosW7bsvvWXLl1KqVKl6NixIwAjRoxgxYoVBAUFUaNGDW7evMmuXbsIDQ2lQYMGuT4P4eHhAMafwdChQ1m8eDG9e/fmrbfeYt++fcyYMYPQ0FBjf6GWLVsyZ84cTp06Ra1atQDYuXMnarWanTt38uabbxrnAbRq1QowtIK88MIL7Nq1i+HDh+Pv78+JEyeYM2cOZ8+eZfXq1Sa1bd26lWXLlhEUFIS7u7vxw/Neu3btIi4ujrFjx6LRaB77nnP6s8/26aefolarmTBhAgkJCcycOZP+/fuzb98+wBBiO3bsSEZGBqNHj8bLy4urV6+ybt064uPjcXZ2fmxND9K3b1/8/f359NNPWb9+PZ988gmurq4sXLiQZ555hs8++4zff/+dCRMm0KhRI+N5zjZ9+nRUKhVvv/02MTExfPnll7Rv356jR49ia2vLe++9R0JCAleuXGHOnDkAODg4PLSezZs306lTJypWrMjUqVNJS0vj66+/pnnz5hw+fPi+n0+fPn3w8/NjxowZHD58mB9++AFPT08+++yzJzofoghShChgCQkJCqB069Ytx9uUL19e6dChgxIbG6vExsYqx44dU/r166cAyujRo03W69y58wP3ceDAAQVQfv7550cea9u2bQqgLF++/KHrjB07VgGUnTt3GuclJSUpfn5+SoUKFRSdTqcoiqJkZWUpGRkZJtveunVLKV26tPLaa68Z561evVoBlJkzZxrnZWVlKS1btsxRzZMnT1YsLS2VuLg447yMjAzFxcXF5DjOzs7KqFGjHrmvB/n5558VQNm8ebMSGxurREZGKn/++afi5uam2NraKleuXFGOHj2qAMrQoUNNtp0wYYICKFu3blUURVFiYmIUQJk/f76iKIoSHx+vqNVq5cUXX1RKly5t3O7NN99UXF1dFb1eryiKovz666+KWq02OeeKoigLFixQAGX37t3GeYCiVquVU6dOPfa9zZ07VwGUVatW5ehc5PRnn/175O/vb/I7kH28EydOKIqiKEeOHHns79vFixcf+nsAKB9++KFx+sMPP1QAZfjw4cZ5WVlZStmyZRWVSqV8+umnxvm3bt1SbG1tlUGDBhnnZdddpkwZJTEx0Th/2bJlCqDMnTvXOK9z585K+fLlc1RvvXr1FE9PT+XmzZvGeceOHVPUarUycODA++q/+/dWURSlR48eipub2wPPjyie5BKPKHCJiYkAODo65mq7//77Dw8PDzw8PKhbty7Lly9nwIABZvmLasOGDTRu3JgWLVoY5zk4ODB8+HAuXbrE6dOnAdBoNFhZWQGGFoC4uDiysrIICAgwuayyYcMGLCwsGDlypHGeRqNh9OjROaqnb9++aLVaVq5caZz333//ER8fT9++fY3zXFxc2LdvH9euXXui992+fXs8PDzw9fWlX79+ODg4sGrVKsqUKcOGDRsAwyWcu2V3bM6+BOLh4UH16tXZsWMHALt370aj0TBx4kSio6M5d+4cYGhBadGihfGSy/Lly/H396d69ercuHHD+Mq+zHTvZbPWrVtTo0aNx76n3P4+5vRnn+3VV181/g6AoQUJDJeJAGMLyb///punlzCGDh1q/F6j0RAQEICiKAwZMsQ438XFhWrVqhlrudvAgQNNzknv3r3x9vY2/pxz4/r16xw9epTBgwfj6upqnF+nTh2effbZB+7z3n5lLVu25ObNm8aflyj+JKCIAufk5AQY+kPkRpMmTdi0aRObN29mz5493Lhxg19++QVbW9tc7edBfQxy6/Lly1SrVu2++f7+/sbl2RYvXkydOnWwsbHBzc0NDw8P1q9fb+xfkL2+t7f3fU3kDzrGg9StW5fq1auzdOlS47ylS5fi7u5u/AAHQ9+fkydP4uvrS+PGjZk6deoDP5weZt68eWzatIlt27Zx+vRpLly4YLx8dPnyZdRqNZUrVzbZxsvLCxcXF5Nz0rJlS+MlnJ07dxIQEEBAQACurq7s3LmTxMREjh07ZvwwB0M/jVOnThlDavaratWqAMTExJgc18/PL0fvKbe/j7n52QOUK1fOZLpUqVIA3Lp1y1jn+PHj+eGHH3B3d6djx47MmzfP5PfjSdx7XGdnZ2xsbHB3d79vfnYtd6tSpYrJtEqlonLlyly6dCnXtWSfk4edtxs3bpCSkvLI+u89b6L4kz4oosA5OTnh4+PDyZMnc7Wdu7s77du3f+Q6NjY2JuOn3C37r9OCvLvgt99+Y/DgwXTv3p2JEyfi6emJRqNhxowZxv4beaVv375Mnz6dGzdu4OjoyN9//81LL71kcvdJnz59jOPH/Pfff8yaNYvPPvuMlStX0qlTp8ceo3Hjxsa7eB4mJwGwRYsWfP/991y4cIGdO3fSsmVLVCoVLVq0YOfOnfj4+KDX600Cil6vp3bt2nzxxRcP3Kevr6/JdE6Da/Xq1QE4ceIE3bt3z9E2ufGwfi3KXZ2EZ8+ezeDBg1mzZg3//fcfb775JjNmzGDv3r2ULVv2oedUp9Pl6rg5qaWwKEq1ivwhLSjCLLp06UJ4eDghISF5ut/y5ctz9uzZBy4LCwszrpMXx8ne393OnDljcowVK1ZQsWJFVq5cyYABA+jYsSPt27cnPT39vv1dv36d5OTkB9acE3379iUrK4u//vqLjRs3kpiYSL9+/e5bz9vbmzfeeIPVq1dz8eJF3NzcmD59eo6P8zDly5dHr9cbL9Fki46OJj4+3uS8ZwePTZs2ceDAAeN0q1at2LlzJzt37sTe3p6GDRsat6lUqRJxcXG0a9eO9u3b3/fKaWvTvVq0aEGpUqX4448/HvmBf/f7zMnPPrdq167N+++/z44dO9i5cydXr15lwYIFwJ3Wg3vv6rq3tSYv3ftzVBSF8+fPm3RmzWlrZPY5edh5c3d3x97e/smLFcWSBBRhFpMmTcLe3p6hQ4c+cCTS8PBw5s6dm+v9Pv/881y5cuW+OzoyMjKMdwE8yd0qDzrO/v37TQJWSkoK3333HRUqVDD2fcj+K/Duv/r27dt3XzB7/vnnycrKMrmlVqfT8fXXX+e4Jn9/f2rXrs3SpUtZunQp3t7eJndm6HS6+y4beHp64uPjc99tuk/i+eefB7hvZNHsFo/OnTsb5/n5+VGmTBnmzJmDVqulefPmgCG4hIeHs2LFCpo2bXpf68/Vq1f5/vvv7zt2WlrafZcIcsrOzo63336b0NBQ3n777Qf+hf7bb7+xf/9+4/vMyc8+pxITE8nKyjKZV7t2bdRqtfHn4uTkhLu7u7HfTrb58+fn6li58csvv5hc9lqxYgXXr183aWmzt7fP0aUob29v6tWrx+LFi01C1smTJ/nvv/+MvztC3E0u8QizqFSpEkuWLDHeCnn3SLJ79uxh+fLlDB48ONf7HT58OD/99BMvvvgir732GvXr1+fmzZssXbqUkydP8ssvv5h0WHyUv/76y/hX8d0GDRrEO++8wx9//EGnTp148803cXV1ZfHixVy8eJG//voLtdqQ/bt06cLKlSvp0aMHnTt35uLFiyxYsIAaNWqYtJZ07dqV5s2b884773Dp0iVq1KjBypUrc90PoW/fvkyZMgUbGxuGDBlirAMMfSzKli1L7969qVu3Lg4ODmzevJkDBw7cNxbGk6hbty6DBg3iu+++Iz4+ntatW7N//34WL15M9+7dadu2rcn6LVu25M8//6R27drGFoIGDRpgb2/P2bNnefnll03WHzBgAMuWLWPEiBFs27aN5s2bo9PpOHPmDMuWLePff/997OWnh8keuXj27Nls27aN3r174+XlRVRUFKtXr2b//v3s2bMHIMc/+5zaunUrQUFBvPjii1StWpWsrCx+/fVXNBoNvXr1Mq43dOhQPv30U4YOHUpAQAA7dux4aGthXnB1daVFixa8+uqrREdH8+WXX1K5cmWGDRtmXKdhw4YsXbqU8ePH06hRIxwcHOjatesD9zdr1iw6depEYGAgQ4YMMd5m7OzsbDKOixBGZryDSAjl7NmzyrBhw5QKFSooVlZWiqOjo9K8eXPl66+/VtLT043rPer24XvdunVLGTdunOLn56dYWloqTk5OStu2bZWNGzfmaPvs2ywf9sq+vTQ8PFzp3bu34uLiotjY2CiNGzdW1q1bZ7IvvV6v/O9//1PKly+vWFtbK/Xr11fWrVunDBo06L7bM2/evKkMGDBAcXJyUpydnZUBAwYYb0F93G3G2c6dO2esc9euXSbLMjIylIkTJyp169ZVHB0dFXt7e6Vu3brG230fJfs24wMHDjxyPa1Wq0ybNs147n19fZXJkyeb/CyzzZs3TwGUkSNHmsxv3769Aihbtmy5b5vMzEzls88+U2rWrKlYW1srpUqVUho2bKhMmzZNSUhIMK4HPNHt1CtWrFA6dOiguLq6KhYWFoq3t7fSt29fJTg42GS9nPzsH3a7+r234F64cEF57bXXlEqVKik2NjaKq6ur0rZtW2Xz5s0m26WmpipDhgxRnJ2dFUdHR6VPnz7GW7YfdJtxbGysyfaDBg1S7O3t73vPrVu3VmrWrHlf3X/88YcyefJkxdPTU7G1tVU6d+6sXL582WTb5ORk5eWXX1ZcXFwUwPg7/bDbojdv3qw0b95csbW1VZycnJSuXbsqp0+fNlnnYfVn/w5evHjxvvcgiieVokiPIyGEEAbBwcG0bduW5cuX07t3b3OXI0ow6YMihBBCiEJHAooQQgghCh0JKEIIIYQodKQPihBCCCEKHWlBEUIIIUShIwFFCCGEEIVOkRyoTa/Xc+3aNRwdHfPkwW9CCCGEyH+KopCUlISPj89jBzUskgHl2rVr9z0YTAghhBBFQ2RkJGXLln3kOkUyoDg6OgKGN5j9qHQhhBBCFG6JiYn4+voaP8cfpUgGlOzLOk5OThJQhBBCiCImJ90zpJOsEEIIIQodCShCCCGEKHQkoAghhBCi0JGAIoQQQohCRwKKEEIIIQodCShCCCGEKHQkoAghhBCi0JGAIoQQQohCRwKKEEIIIQodCShCCCGEKHQkoAghhBCi0JGAIoQQQohCp0g+LFAIIUTxoygK6Vo9ielaEtO0JKZr8Xa2xcfF1tylCTOQgCKEECJPKIpCmlZHYlqWScgwnc4iMU1LUvr98xLTtWh1isk+NWoVH3T2Z1CzCjl6Aq4oPiSgCCGEuE9cSibhscmPDBMPCh5ZeuXxO38MtQqcbC2xsdAQlZjO1LWnOXUtkU961MLaQpMH704UBRJQhBBCmNgTfoMhiw6SptU90fYatQonGwucbC1xsrHEydbC8PXu723v+f6uZXZWGlQqFYqi8MPOi8zYGMryQ1c4F5PMwgENKe1kk8fvWBRGKkVRnj7uFrDExEScnZ1JSEjAycnJ3OUIIUSxcSwynpe/30tKpo7STtaUdrK5P1jcDh+ONo8OGHllx9lYRv9xhIQ0LZ6O1iwY0JAG5Url2f5FwcnN57cEFCGEEACcj0nixQUh3ErV0qySGz8NboSNZeG4pHL5ZgrDfjnI2ehkrDRqPulRiz4BvuYuS+RSbj6/5TZjIYQQXLmVyoAf93MrVUvdss58NzCg0IQTgPJu9qx8ozkdapQmU6dn0orjTP37FFqd3tyliXwiAUUIIUq4G8kZDPhxP9cT0qns6cDPrzbGwbrwdVF0sLZgwSsNGdu+CgCL9lxiwI/7iEvJNHNlIj9IQBFCiBIsMV3LoJ/2c/FGCmVcbPl1SGNc7a3MXdZDqdUqxravysIBDbG30rD3Qhxdv97FqWsJ5i5N5DEJKEIIUUKla3UMXXyQU9cScbO34tchjfF2LhqDonWs6cWqUc2p4GbH1fg0en27h7XHrpm7LJGHJKAIIUQJpNXpGfX7YfZfjMPR2oLFrzWmooeDucvKlaqlHVkzqgUtq7iTrtUz+o8jzPznDLo8GItFmJ8EFCGEKGH0eoVJK46z5UwM1hZqfhgUQK0yzuYu64k421my6NXGvN6qIgDzg8MZuvgACWlaM1cmnpYEFCGEKEEUReGjdadZdeQqGrWK+f0b0KSim7nLeioatYrJz/vzZd96WFuo2RYWS495uzkfk2zu0sRTkIAihBAlyNwt51i05xIAs1+sSzv/0uYtKA91r1+GFSOa4eNsw4UbKfSYt5stodHmLks8IQkoQghRQizafZEvN58DYGrXGnSvX8bMFeW92mWd+Xt0CxpXcCUpI4uhvxzkm63nKIJjkpZ4ElCEEKIEWHXkClPXngZgbPsqDG7uZ+aK8o+7gzW/DW3CK03LoSjw+X9nGbXkMCkZWeYuTeSCBBQhhCjmtoRGM2H5cQAGN6vAmHZVzFxR/rOyUPNJ99rM6FkbS42KDSei6PXtHiLjUs1dmsghCShCCFGM7btwkzd+P4xOr9CjfhmmdKmRpw/yK+xealyOP4Y1xd3BmjNRSXT9Zhe7z98wd1kiBySgCCFEMXXyagJDFx8kI0tPe39PZvaug1pdcsJJtoAKrqwd3Zw6ZZ2JT9Uy8Kf9/LjrovRLKeQkoAghRDF0ITaZQT/tJykji8Z+rnzzcgMsNSX3v3xvZ1uWvR5Iz/pl0OkVPl53mgnLj5Ou1Zm7NPEQJfe3VQghiqnrCWkM+HE/N1MyqenjxA+DCteTic3FxlLD7D51+aBLDdQq+OvwFfp+t5eohHRzlyYeQAKKEEIUI3Epmbzywz6uxqdR0d2exa81xsnG0txlFRoqlYohLfz45bUmONtaciwynq7f7OLQ5ThzlybuIQFFCCGKieSMLAb/vJ/w2BS8nW34ZUhj3B2szV1WodSiijtrg1pQrbQjsUkZ9PtuL3/ujzB3WeIuElCEEKIYSNfqGP7LQY5fSaCUnSW/DmlM2VJ25i6rUCvnZsfKN5rRqZYXWp3COytP8MHqk2h1enOXJpCAIoQQRV6WTs+bfxxhT/hN7K00LH6tMZU9Hc1dVpFgb23BvJcb8NazVQH4de9l+v+wjxvJGWauTOQqoHz77bfUqVMHJycnnJycCAwMZOPGjcbl6enpjBo1Cjc3NxwcHOjVqxfR0abPQYiIiKBz587Y2dnh6enJxIkTycqS0f2EEOJJ6PWGv/z/Ox2NlYWa7wcFUKesi7nLKlLUahWj21Xh+4EBOFhbsP9iHN2+2c3JqwnmLq1Ey1VAKVu2LJ9++imHDh3i4MGDPPPMM3Tr1o1Tp04BMG7cONauXcvy5cvZvn07165do2fPnsbtdTodnTt3JjMzkz179rB48WIWLVrElClT8vZdCSFECaAoCv/bEMqKQ1dQq+Drl+rTrJK7ucsqsp6tUZrVo5rh527P1fg0ei/Yw5qjV81dVomlUp5ypBpXV1dmzZpF79698fDwYMmSJfTu3RuAM2fO4O/vT0hICE2bNmXjxo106dKFa9euUbq04QmaCxYs4O233yY2NhYrK6scHTMxMRFnZ2cSEhJwcnJ6mvKFEKLImrftPLP+DQNgVu86vBjga+aKioeENC1v/nGE7WdjAXi9dUUmdayOpgQOcpfXcvP5/cR9UHQ6HX/++ScpKSkEBgZy6NAhtFot7du3N65TvXp1ypUrR0hICAAhISHUrl3bGE4AOnbsSGJiorEV5kEyMjJITEw0eQkhREn2297LxnDyfmd/CSd5yNnWkp8GN2JE60oALNx+gdcWHSAhVWvmykqWXAeUEydO4ODggLW1NSNGjGDVqlXUqFGDqKgorKyscHFxMVm/dOnSREVFARAVFWUSTrKXZy97mBkzZuDs7Gx8+frKP0QhRMn197FrfLDmJABBbSsztGVFM1dU/GjUKt7pVJ2vXqqPjaWa7Wdj6TZvF+eik8xdWomR64BSrVo1jh49yr59+xg5ciSDBg3i9OnT+VGb0eTJk0lISDC+IiMj8/V4QghRWAWHxTB+6VEUBV5pWo63OlQ1d0nF2gt1fVgxohllXGy5dDOVHvP3sOl09OM3FE8t1wHFysqKypUr07BhQ2bMmEHdunWZO3cuXl5eZGZmEh8fb7J+dHQ0Xl5eAHh5ed13V0/2dPY6D2JtbW28cyj7JYQQJc3BS3GM+O0QWXqFrnV9+OiFWiXqycTmUquMM38HNaexnyvJGVkM++UgX205h14vDxvMT089DoperycjI4OGDRtiaWnJli1bjMvCwsKIiIggMDAQgMDAQE6cOEFMTIxxnU2bNuHk5ESNGjWethQhhCi2Qq8n8tqiA6Rr9bSu6sHsF+uWyCcTm4ubgzW/D23CwMDyAHyx6Sxv/H6YlAwZJiO/WORm5cmTJ9OpUyfKlStHUlISS5YsITg4mH///RdnZ2eGDBnC+PHjcXV1xcnJidGjRxMYGEjTpk0B6NChAzVq1GDAgAHMnDmTqKgo3n//fUaNGoW1tQzHLIQQD3LpRgoDftxPYnoWAeVLseCVhlhZyDibBc1So+ajbrWo6ePE+6tP8s+pKC7OT+G7gQ0p72Zv7vKKnVwFlJiYGAYOHMj169dxdnamTp06/Pvvvzz77LMAzJkzB7VaTa9evcjIyKBjx47Mnz/fuL1Go2HdunWMHDmSwMBA7O3tGTRoEB999FHevishhCgmohPTeeVHw8im1b0c+XFwI2yt5MnE5tS3UTkqezoy4rdDhEUn8cI3u5n3cgNaVJExaPLSU4+DYg4yDooQoiSIT82kz8IQzkYnU97NjuUjAvF0tDF3WeK2qIR0Xv/tEMci41Gr4N3n/RnSwk/6BT1CgYyDIoQQIv+kZGTx6qIDnI1OprSTNb8NaSLhpJDxcrZh6fCm9GpQFr0Cn6wP5a1lx0jX6sxdWrEgAUUIIQqZjCwdI347xJGIeJxtLfnltSb4usqTiQsjG0sNn79YhyldaqBRq1h55Cp9FoZwPSHN3KU9leSMLBLSzDswnQQUIYQoRHR6hfFLj7Hz3A3srDT8/GojqnnJk4kLM5VKxWst/Pj1tca42Fly/EoCXb/ezcFLceYuLccURSE8Npkfdl6g/w97qf/Rf/y297JZa8pVJ1khhBD5R1EU3l99gvUnrmOpUbFwQEMalCtl7rJEDjWr7M7aoBYM++UgZ6KSeOn7vUx7oRYvNyln7tIeKF2rY9/FOLadiWFbWAyXb6aaLD993byPlZFOskIIUUh8uvEMC7aHo1bBNy834Pna3uYuSTyB1MwsJi4/zvoT1wHo36QcH3atWShuDb8an8a2MzEEh8Ww+/xN0u7qL2OpUdHEz4221T1pW82Dih4OeX783Hx+SwuKEEIUAgu3h7NgezgA/+tRW8JJEWZnZcE3L9enRrATn/8Xxu/7IjgbncT8/g3xcCzYMb+0Oj2HL99ia1gMwWdiCbvnWUJeTja0re5B22qeNK/sjr114YkF0oIihBBm9uf+CN5ZeQKAdzpVNz5FVxR9W89EM+aPoyRlZOHtbMN3AwKoXdY5X495IzmD4LBYtoXFsONsLEnpd0a7VaugQblSt1tJPPH3dizQ26Jz8/ktAUUIIcxo44nrjFpyGL0CI1pX4p1O1c1dkshj52OSGf7LQS7cSMHaQs1nverQvX6ZPNu/Xq9w4moCW29fujl2JcFkeSk7S9pU86RNNQ9aV/XAxc4qz46dWxJQhBCiCNh5LpYhiw6SqdPzUmNf/tejtgzyVUwlpGkZ++cRtoXFAjC8VUXefq46mid8nlJCmpad52LZdiaW7WdjuJGcabK8VhknnqnmSZvqntQt6/LEx8lrElCEEKKQOxJxi/4/7CM1U8fztb34+qUGheZDROQPnV7hi01hzNtm6GvUsoo7X79UP0ctGoqicDY6mW1hMWw9E8Ohy7fQ3fU0ZQdrC1pWcaft7ZYST6fCOaifBBQhhCjEzkYn8eKCEBLStLSs4s4PgwKwtpDn65QU645fY+Ly46RpdZR3s+P7gQFULX3/WDepmVmEhN+8fekmlqvxpoO/VfZ0oG01D9pW9ySgvGuhuEvoceQuHiGEKKQi41IZ8OM+EtK01C/nwoJXGko4KWG61PGhorsDw345yOWbqfSYt5sv+tajY00vIm6msvVMNNvCYgm5cJPMLL1xO2sLNYGV3HjmdgfX4j66sLSgCCFEAYlJSufFBSFcvplK1dIOLHs90KwdFoV5xaVkMur3w4RcuAlAOVc7IuJMB0sr42JrCCTVPQis6F7kn2QtLShCCHEPvV4hS6+QpdcbvuoUsnR3vtfq9ej0Clqd3rBMf9fy299rdQq62/swfG/4eu96JvvU3TluSPhNLt9MpWwpW34d0kTCSQnnam/FL0MaM319KIv2XCIiLhULtYqACqWMrSSVPR1KbMdpCShCFFFxKZnsOBvL8SsJ6IteQ+h9FEVBp9z+YM/+8L/9gW8IDrfDxb3h4a5wYdj2rqBxV2jQF5JT5O5geDJx6ULaiVEULEuNmqkv1KRtdU/SMrNoVtkdJxtLc5dVKEhAEaKI0OkVjl2JJzgslu1nYzl+JZ5ikEvMSqUCS7UaC40KC7UKC40aC7UKS40ajVqFhUaFpdrwvaXGsNz4vVp9e5s721mo1VhqVLfXMczT3N6HhUaFjaWGLnW8KVuqePcdELnXuqqHuUsodCSgCFGI3UjOYMfZWILDYtl5LpZbqaaPP6/u5UhgJTfsrYrHP2WN+k5QyP6gt9CosVTf9aGfHSaMwcLw1bC+acCwNAkPd31/OzSo5bZeIQqt4vG/mhDFhE6vcDTyFsFhhlBy4qrpiJCONoaxDlpX9aB1VU+8nOUygRCieJKAIoSZxSSls+PsDYLDYth57gYJaaatJDW8nWhTzYM21TypX84FS03hH+tACCGelgQUIQpYlk7Pkch4gsMMgy+dupZostzJxoKWVT1oU9Xw3IzCOiKkEELkJwkoQhSA6MR0tp+NZfvtviSJdz1dFKB2GWdaV/WgTTUP6vm6YCGtJEKIEk4CihD5QKvTc/jyLYJvd3ANvW7aSuJiZ0nLKoZWklZVPfBwtDZTpUIIUThJQBEij0QlpBMcFsP2s7HsOneDpIw7rSQqFdQp40zrap60rmpoJZEHwwkhxMNJQBHiCWl1eg5eukXw2Ri2h8VyJirJZHkpO0ta3b5s06qKB24O0koihBA5JQFFiFy4Fp92e6C0GHafv0nyPa0kdcu6GO+4qV3GWVpJhBDiCUlAEeIRMrP0HLwUd7svSQxno5NNlrvZWxnGJKnmQcsqHrjay7NVhBAiL0hAEeIe1xPS2BJquAV4T/gNUjN1xmVqFdTzdaFNNU/aVPOglo+zjEYqhBD5QAKKEHc5cSWBPgtDSNPeCSXuDtbGW4BbVnGXJ9AKIUQBkIAixF2+2BRGmlZHFU8HutXzoU01T2p4O0kriRBCFDAJKELcdvJqAtvCYlGr4PuBAVRwtzd3SUIIUWLJcJVC3PbN1vMAvFDXR8KJEEKYmQQUIYCz0Un8cyoKgFFtK5u5GiGEEBJQhADmbTO0nnSq5UWV0o5mrkYIIYQEFFHiXbyRwtpj1wBpPRFCiMJCAooo8b4NPo9egWeqe1KrjLO5yxFCCIEEFFHCXbmVysrDVwFpPRFCiMJEAooo0RZuv0CWXqF5ZTcali9l7nKEEELcJgFFlFjRieksPRgJwOhnqpi5GiGEEHeTgCJKrO93XCAzS0+jCqVo4udq7nKEEELcRQKKKJFuJmfw+74IAIKeqYJKJUPZCyFEYZKrgDJjxgwaNWqEo6Mjnp6edO/enbCwMJN12rRpg0qlMnmNGDHCZJ2IiAg6d+6MnZ0dnp6eTJw4kaysrKd/N0Lk0E+7L5Km1VGnrDOtqribuxwhhBD3yNWzeLZv386oUaNo1KgRWVlZvPvuu3To0IHTp09jb39naPBhw4bx0UcfGaft7OyM3+t0Ojp37oyXlxd79uzh+vXrDBw4EEtLS/73v//lwVsS4tESUrUs3nMZgKC2laX1RAghCqFcBZR//vnHZHrRokV4enpy6NAhWrVqZZxvZ2eHl5fXA/fx33//cfr0aTZv3kzp0qWpV68eH3/8MW+//TZTp07FykoeZS/y16I9l0jOyKK6lyPt/UubuxwhhBAP8FR9UBISEgBwdTXtYPj777/j7u5OrVq1mDx5MqmpqcZlISEh1K5dm9Kl73wwdOzYkcTERE6dOvXA42RkZJCYmGjyEuJJJGdk8dPui4Bh3BO1WlpPhBCiMMpVC8rd9Ho9Y8eOpXnz5tSqVcs4/+WXX6Z8+fL4+Phw/Phx3n77bcLCwli5ciUAUVFRJuEEME5HRUU98FgzZsxg2rRpT1qqEEa/7b1MQpqWiu72PF/b29zlCCGEeIgnDiijRo3i5MmT7Nq1y2T+8OHDjd/Xrl0bb29v2rVrR3h4OJUqVXqiY02ePJnx48cbpxMTE/H19X2ywkWJlZap44edFwB4o21lNNJ6IoQQhdYTXeIJCgpi3bp1bNu2jbJlyz5y3SZNmgBw/rzhabFeXl5ER0ebrJM9/bB+K9bW1jg5OZm8hMitPw9EcCM5k7KlbOlWz8fc5QghhHiEXAUURVEICgpi1apVbN26FT8/v8duc/ToUQC8vQ3N6YGBgZw4cYKYmBjjOps2bcLJyYkaNWrkphwhciwjS8fC7YbWk5FtKmGpkSGAhBCiMMvVJZ5Ro0axZMkS1qxZg6Ojo7HPiLOzM7a2toSHh7NkyRKef/553NzcOH78OOPGjaNVq1bUqVMHgA4dOlCjRg0GDBjAzJkziYqK4v3332fUqFFYW1vn/TsUAvjr0FWiEtMp7WRN74aPbvUTQghhfrn6M/Lbb78lISGBNm3a4O3tbXwtXboUACsrKzZv3kyHDh2oXr06b731Fr169WLt2rXGfWg0GtatW4dGoyEwMJBXXnmFgQMHmoybIkRe0ur0zA82XGJ8vVUlrC00Zq5ICCHE4+SqBUVRlEcu9/X1Zfv27Y/dT/ny5dmwYUNuDi3EE/v76DWu3ErDzd6KlxqXM3c5QgghckAuxItiTadXmHe79WRoy4rYWknriRBCFAUSUESxtvHkdS7EpuBsa8krTaX1RAghigoJKKLY0usVvtlqaD15tXkFHG0szVyREEKInJKAIoqtLWdiOBOVhIO1BYObVTB3OUIIIXJBAooolhRF4Zut5wAYEFgeFzt5CKUQQhQlElBEsbTz3A2OXUnAxlLNkBaPH1BQCCFE4SIBRRRL2X1P+jcpj7uDDAAohBBFjQQUUezsu3CT/ZfisNKoGd6qornLEUII8QQkoIhi55tthtaTPo3KUtrJxszVCCGEeBISUESxciTiFjvP3cBCreL1VpXMXY4QQognJAFFFCvzbree9KhfBl9XOzNXI4QQ4klJQBHFxqlrCWwOjUGtgpFtpPVECCGKMgkootjIbj3pUseHih4OZq5GCCHE05CAIoqFc9FJbDwZBcCotpXNXI0QQoinJQFFFAvzg8NRFOhYszTVvBzNXY4QQoinJAFFFHmXb6aw5uhVAILaVjFzNUIIIfKCBBRR5H0bHI5egTbVPKhd1tnc5QghhMgDElBEkXY1Po2/Dl8BYPQz0vdECCGKCwkookj7bns4Wp1CYEU3GpZ3NXc5Qggh8ogEFFFkxSSl88eBSEBaT4QQoriRgCKKrB92XiQzS0+Dci4EVnIzdzlCCCHykAQUUSTFpWTy297LAIx+pgoqlcrMFQkhhMhLElBEkfTz7oukZuqo6eNEm2oe5i5HCCFEHpOAIoqchDQti3ZfAgx9T6T1RAghih8JKKLI+TXkEkkZWVQt7UCHGl7mLkcIIUQ+kIAiipSUjCx+3HURMDxzR62W1hMhhCiOJKCIImXJvghupWrxc7enSx0fc5cjhBAin0hAEUVGulbHdzsvADCyTSU00noihBDFlgQUUWQsOxhJbFIGZVxs6VG/jLnLEUIIkY8koIgiITNLz4LgcABGtKmEpUZ+dYUQojiT/+VFkbDqyBWuJaTj6WjNiw3LmrscIYQQ+UwCiij0snR65t9uPRneqiI2lhozVySEECK/SUARhd7a49e4fDMVV3srXm5SztzlCCGEKAASUEShptcrfLP1PABDWvhhZ2Vh5oqEEEIUBAkoolD751QU4bEpONlYMDCwvLnLEUIIUUAkoIhCS1EUvr7dejK4uR+ONpZmrkgIIURBkYAiCq2tZ2IIvZ6IvZWGV5tVMHc5QgghCpAEFFEo3d168kpgeUrZW5m5IiGEEAVJAooolHafv8nRyHisLdQMbVHR3OUIIYQoYBJQRKH09dZzALzUuBwejtZmrkYIIURBk4AiCp39F+PYdzEOS42K11tL64kQQpREuQooM2bMoFGjRjg6OuLp6Un37t0JCwszWSc9PZ1Ro0bh5uaGg4MDvXr1Ijo62mSdiIgIOnfujJ2dHZ6enkycOJGsrKynfzeiWPhmm6HvSe+Gvng725q5GiGEEOaQq4Cyfft2Ro0axd69e9m0aRNarZYOHTqQkpJiXGfcuHGsXbuW5cuXs337dq5du0bPnj2Ny3U6HZ07dyYzM5M9e/awePFiFi1axJQpU/LuXYki61hkPDvOxqJRqxjZupK5yxFCCGEmKkVRlCfdODY2Fk9PT7Zv306rVq1ISEjAw8ODJUuW0Lt3bwDOnDmDv78/ISEhNG3alI0bN9KlSxeuXbtG6dKlAViwYAFvv/02sbGxWFk9/m6NxMREnJ2dSUhIwMnJ6UnLF4XQsF8Osul0ND0blOGLPvXMXY4QQog8lJvP76fqg5KQkACAq6srAIcOHUKr1dK+fXvjOtWrV6dcuXKEhIQAEBISQu3atY3hBKBjx44kJiZy6tSpBx4nIyODxMREk5cofkKvJ7LpdDQqFYxqW9nc5QghhDCjJw4oer2esWPH0rx5c2rVqgVAVFQUVlZWuLi4mKxbunRpoqKijOvcHU6yl2cve5AZM2bg7OxsfPn6+j5p2aIQm3e770nn2t5U8nAwczVCCCHM6YkDyqhRozh58iR//vlnXtbzQJMnTyYhIcH4ioyMzPdjioIVHpvM+hPXAWk9EUIIAU/0aNigoCDWrVvHjh07KFu2rHG+l5cXmZmZxMfHm7SiREdH4+XlZVxn//79JvvLvssne517WVtbY20tY2EUZ/O3haMo8GyN0vh7S78iIYQo6XLVgqIoCkFBQaxatYqtW7fi5+dnsrxhw4ZYWlqyZcsW47ywsDAiIiIIDAwEIDAwkBMnThATE2NcZ9OmTTg5OVGjRo2neS+iiIqMS2X10asABEnriRBCCHLZgjJq1CiWLFnCmjVrcHR0NPYZcXZ2xtbWFmdnZ4YMGcL48eNxdXXFycmJ0aNHExgYSNOmTQHo0KEDNWrUYMCAAcycOZOoqCjef/99Ro0aJa0kJdS328PR6RVaVfWgrq+LucsRQghRCOQqoHz77bcAtGnTxmT+zz//zODBgwGYM2cOarWaXr16kZGRQceOHZk/f75xXY1Gw7p16xg5ciSBgYHY29szaNAgPvroo6d7J6JIup6QxoqDVwAY/Yy0ngghhDB4qnFQzEXGQSk+pq09xc+7L9HEz5WlrweauxwhhBD5qMDGQRHiacQmZfDH/ggARj9TxczVCCGEKEwkoAiz+WHXBdK1eur5utC8spu5yxFCCFGISEARZnErJZPfQi4Dhr4nKpXKzBUJIYQoTCSgCLP4ec8lUjJ1+Hs78Ux1T3OXI4QQopCRgCIKXGK6lkW7LwLSeiKEEOLBJKCIAvdryGUS07Oo7OnAczUfPHqwEEKIkk0CiihQqZlZ/LjL0Hoyqm0l1GppPRFCCHE/CSiiQC3ZF0FcSiblXO3oWsfH3OUIIYQopCSgiAKTrtXx3Y4LALzRphIWGvn1E0II8WDyCSEKzPJDV4hJysDb2YaeDco+fgMhhBAllgQUUSC0Oj0LgsMBGNG6ElYW8qsnhBDi4eRTQhSIVUeucjU+DQ9Ha/o28jV3OUIIIQo5CSgi3+n0CvO3nQdgeMuK2FhqzFyREEKIwk4Cish3645f49LNVErZWfJyk3LmLkcIIUQRIAFF5Cu9XmHe7daTIS38sLe2MHNFQgghigL5tBD5QqvTs/VMDEv2RXA2OhlHGwsGNqtg7rKEEEIUERJQRJ4Kj01m2YFI/jp8lRvJGcb5bz1bFScbSzNWJoQQoiiRgCKeWmpmFuuPX2fZwUgOXLplnO/uYEWvhmXpE+BLJQ8HM1YohBCiqJGAIp6IoigcjYxn2cFI1h67TnJGFgBqFbSt5kmfRr48U90TSxktVghQFLi0Ew7+DNo0sLQBC9uHfLUBS1vD66Hr3PVVYwnyRHBRDElAEbkSl5LJqiNXWXrA0LckW3k3O/oE+NK7YVlKO9mYsUIhChFFgYs7IPhTiNiTP8dQqR8fdu79mtPwY+8GTmUMIUiIAiYBRTyWTq+w6/wNlh2I5L/TUWh1CgDWFmqer+1N30a+NPFzRSV/xQlhoChwIRi2fwYRIYZ5GitoMBC8aoM2HbLSDF+1qZCVbmhZMfl61zoP+mo8lh60KYZXflCpwdEbnH3Bxfeur+Vufy0LVvb5c2xRoklAEQ8VGZfK8kNXWHEwkmsJ6cb5tcs406eRLy/U9cHZVv6yEsJIUeDCNgj+DCL3GuZprKHhIGg+FpzL5N1xsjIeHmC0aY8ONzn5qk2DlBjQZULiVcMr+z3dy87tAcHlrkBjW0ouQ+UhvaInPSuddF06GVkZpOnSDNO35939fVpWGhm6DOO8u6eztzNOZ6UZt8/QZdCzSk/eafyO2d6nBBRhIiNLx3+noll2MJJd52+gGBpLcLa1pEf9MvQJ8KWGj5N5ixSisFEUCN9quJRzZb9hnsYaGg6GFmPBySdvj6dSGS7DWNqAbd7u2oRebwgp8ZGQEHH7a6Tp18wkSL1peF0/+uD9WDkYWlpMWmHK3Zl28AJ10eqvptPryNRnkqm7/dJnkqHLQKvTkqkzfH/v8uzvM3QZaPV3rXfX/HsDxoOCRoYu4/EF5oG0u1vqzEACigAg9HoiSw9EsvroVeJTtcb5zSu70SfAl441vWSIeiHupSgQvuV2MDlgmGdhAw1fheZjwMnbvPU9LbUaHL0ML99G9y9XFEiPf0BwiTB8TbgCKbGQmQyxZwyvBx7H0tC6dG9wcfYFh9LGPjGKhTVatQWZKGToM9HqtXc+4O8NADqtMTQ8KCQ8MCg8KlDctT+tTkuWkpWvpz6nrNRW2FjYYKOxMXy9/bLV2GJtYW2cb2thi43GBmsLa+P3xvU1d77aWthiY2GDtcYaJ2vz/jEqAaUES0zX8vfRayw7GMnxKwnG+d7ONrzYsCwvBvji62pnxgqFKKQUBc5vgeAZcPWgYZ6FDQS8Zggmjl7mra+gqFSGyze2pcC7zoPX0aYZgkp2aLkrzKQkRBKbGk2sRkVsZgyxcTeJTTxBrEZjfCVq1GSqVGSiIlNdOC8TqVBhrbHGUmOJldoKa401VhorLDWWWKsN3xtf6od8rzFs99DwcDt0ZIcHWwtbrDXWaNTF9w9HCSgljKIo7L8Yx9KDkWw4cZ10rR4AS42KZ2uUpk+ALy2reKAppP8RCGFWigLnNsH2T+HqIcM8C9u7gklp89ZXCCiKQoo2hdi0WGJTY+//qo0lVhVLrHUcqa4qcH3yMGepKFgrClaKYvK94cVd35u+rG8vu28b7t/OOns9tRVWGmvDy8IaK40NVpY2WFnYYWFhg8rC9sF3TOXoq93tS3Z2d+ZJnx0JKCVFTGI6Kw5fYfnBK1y8cae3fxVPB/o28qVH/TK4OVibsUIhCjFFgXP/GS7lXDtsmGdhC42GQLM3S0QwURSFZG2yMWzEpMZwI+3GfV9j02Jz1XfB3tIeD1sPPOw8cLd1x9PWEw87D+M8Z2tnQ4uEyhIrwEqfhbVej6UuC5Uu4+k6At/39Z67qRTdXZVmAskPeRd5TXUnrGR/tbK7Z172fPs7t45b2t9ZbnXvunZ31rOyN9xVVshDkASUYixLp2dbWCxLD0SwLSwWnd7Q49XeSkPXuj70aeRLfV8XuT1YiIdRFDj7r6HF5NoRw7zsYNJ8DDh4mre+PJKlz+JG2g2iUqKISo0iOiWaqJSo+1o/0nXpj9/ZbQ6WDiZBw8P2nu9vf7WzLMSXkXVa08CSq7ujHnTr+MO+3t5Ol3n7wEr+3joOhtvHLe8JPfeGoEptDR29zUQCSjF0ITaZZQev8NfhK8Qm3entHVC+FH0a+dK5trc8VViIR1EUOPuPocUk+84USztoNNTQYuLgYdbyckOn13Ej7QbRqYbQEZUSdef722EkNi0WvaLP0f4crRwfGDSyv3raeuJu546tRX7eXlRANJa3B6kroM6iuqzbAScNMlPuhCJt9vepkJlq+Jo9fff3mTmYr799E4SiN3ReznxEq5CdW8G874eQT6liIjUziw0nolh2IJL9l+KM890drOjZwPA8nMqe8jwcIR5JUSBso6HF5PoxwzxLe2g8FAJHF7pgolf03Ey7+eDwcfv72NTYHN1xYqGywNPOEy97L0rbl8bLzgtPO8/7AoiNhYwUnW80FqBxBGvH/DuGTnsnvDwyBKWBZ/X8qyMHJKAUYYqicOxKAksPRLL22DWT5+G0qeZJnwBf2vnL83CEeCxFgTPrDSO/Rh03zLO0h8bDoNlosHcv8JL0ip649LgHho/olGiiUw2vLP3jw4dGpcHDzgMvuzvh4+4g4mXvhZutG2qV/F9R7GksQeMMNs7mruSxJKAUQbduPw9n2cFIzkQlGednPw+nV4OyeDnLXzlCPJZeD2HZweSEYZ6VgyGYBI42PIsmHyiKwq2MW8awYez3kRplEkC0eu1j96VWqXG3dTcEDrvSeNl73Qkit793t3Uv1rejiuJJAspdQq8nEhwWi5OtBY42ljjZGL46G6ctsbFUm6VTqf7283CWHoxk06loMnWG68XWFmo61fKiTyNfmvq5oZbbg4V4PL0ezqwzBJPok4Z5Vg7Q5HUIDAI71zw5TEJGAuHx4ZyPP8/5+PNciL/AtZRrRKdEk6nPfOz2KlS427rfCR53h5DbL3dbdyzU8l+5KH7kt/ouRyLi+eyfh4x0eJuFWoWTrSWONhY42Vgawoy15V2h5vayu9ZxtLHA+fa0o41lrsYYuXIrleUHr7Di0BWuxt+5da9WGSf6BvjyQr0y8jwcIXJKr4czaw3Pyok5ZZhn5Xg7mIx64mCSok0xCSLh8eGcv3WemLSYR27nZuP20Esupe1L42nriaU8SViUUBJQ7lLezY6eDcqQlJ5FYprW8DXd8DUpXYtegSy9QlxKJnEpj//r52HsrTT3BRjTaUNLzdYzMSbPw3GysTA8D6eRLzV9Cv/1QyEKDb0eQv82tJjEnDbMs3KEpiOg6Rs5DibpWelcSLhgDCLnbxnCyLWUaw/dxsvei0oulajiUoWKzhUp61jW2BJipbHKi3cnRLEkAeUuzSu707zygzvDKYpCSqbunuCiJTHNEF4Sb8+7e9qw/M762aO2pmTqSMnUcT3hgYe6T7NKbvRtJM/DESLX9Ho4vRp2zLoTTKydoMkIaDryocEkU5fJpcRLnL913qRVJDIpEgXlgdu427obg0gll0pUdqlMJZdKOFrl4x0ZQhRjElBySKVS4WBtgcNTjB+SmaUnKd20ZebuAJN413RSupbqXo70buhLObdCPJCREIWRXmcIJttnQWyoYZ618+0Wk5GGZ8dgGKAsIjHiTovI7SByOfEyOpNRRO9wsXYxho+7w4iLjUvBvDchSggJKAXIykKNm4O1DCkvRH7R6+DUKtg+E26EGeZZO6NrOoKrNV/gfHoM588tN4aRSwmXHnqnjKOloyF8lKpMZZfKxlDiZuMmoy8LUQAkoAghir7bwUTZ/inX4y9w3tKS824ehHvX5JyVBRevriI94o8HbmprYUsl5/uDSGm70hJEhDAjCShCiCJHURRi02I5HxfG+TOrOX9xC+H6VM7bW5LqWObOiikX4PbjTKzUVlRyqWS8JJMdRHwcfGSAMiEKIQkoQohCLS497r7Oqufiz5GUeWeQQqwADJdOLdQWVHCqYNI/pHKpypR1KCuDlQlRhOQ6oOzYsYNZs2Zx6NAhrl+/zqpVq+jevbtx+eDBg1m8eLHJNh07duSff/4xTsfFxTF69GjWrl2LWq2mV69ezJ07FwcHeVaMECVVcmYyZ2+dva/Dalx63APX1ygKvtosquihkldDKtd4kcoetSnnVA5LtYwdIkRRl+uAkpKSQt26dXnttdfo2bPnA9d57rnn+Pnnn43T1tamnUL79+/P9evX2bRpE1qtlldffZXhw4ezZMmS3JYjhCgG/rn0Dx/s+oB0Xfp9y1SoKOtQlkpqG6rEhFMpMYbKmVr8LBywajYaGg/P34erCSHMItcBpVOnTnTq1OmR61hbW+Pl5fXAZaGhofzzzz8cOHCAgIAAAL7++muef/55Pv/8c3x8fHJbkhCiCFt5biXTQqahV/R42nlStVTVO5dnnPyoeOUItru+hLgLhg1sXaHVRMPzciSYCFFs5UsflODgYDw9PSlVqhTPPPMMn3zyCW5uhoduhYSE4OLiYgwnAO3bt0etVrNv3z569Ohx3/4yMjLIyMgwTicmJuZH2UKIAvbLqV+YdXAWAH2q9uG9pu8ZOqzqsuD4Ulg/EG5dNKxs52Z4snCjoRJMhCgB8jygPPfcc/Ts2RM/Pz/Cw8N599136dSpEyEhIWg0GqKiovD09DQtwsICV1dXoqKiHrjPGTNmMG3atLwuVQhhJoqiMP/YfBYcWwDAq7VeZVyDcaj0WXDsd9j5Ody6ZFjZzg2avXk7mEg/NSFKijwPKP369TN+X7t2berUqUOlSpUIDg6mXbt2T7TPyZMnM378eON0YmIivr6+T12rEKLg6RU9sw7M4rfQ3wAY02AMQ2sMgiO/GYakj79sWNHOHZq/CQFDJJgIUQLl+23GFStWxN3dnfPnz9OuXTu8vLyIiTF9wmdWVhZxcXEP7bdibW19X0dbIUTRo9PrmBoyldXnVwPwbqO3eSldga8b3gkm9h7QfAwEvAZW9uYrVghhVvkeUK5cucLNmzfx9vYGIDAwkPj4eA4dOkTDhg0B2Lp1K3q9niZNmuR3OUIIM9HqtLy98202Xd6ERqXh47LP0XXTrDuXcozBZAhYyfOnhCjpch1QkpOTOX/+vHH64sWLHD16FFdXV1xdXZk2bRq9evXCy8uL8PBwJk2aROXKlenYsSMA/v7+PPfccwwbNowFCxag1WoJCgqiX79+cgePEMVUWlYa44LHsfvqbixVGmYl62m341vDQgkmQogHUCmK8uBnhz9EcHAwbdu2vW/+oEGD+Pbbb+nevTtHjhwhPj4eHx8fOnTowMcff0zp0qWN68bFxREUFGQyUNtXX32V44HaEhMTcXZ2JiEhAScnp9yUL4QoYEmZSQRtGcXhmCPYKvBlVAzN0tMNfUxajJVLOUKUILn5/M51QCkMJKAIUTTcSonl9fUvE5oWhaNOz/zoGOppnAwtJo2GSDARooTJzee3PItHCJH3dFlEH/6J4Se+5oIGXHU6FsZnUr3V+4bbhSWYCCEeQwKKECLv6LLg5Aoid3zGMNt0rlpaUFqn5/sKffBrPkFuFxZC5JgEFCHE09Nlwcm/YMdMzideZriXB7EWFpSzdOL7rovwca1i7gqFEEWMBBQhxJPT6+DECtgxE26e56SVFSN8vEhQq6jiXInvOv6Au627uasUQhRBElCEELmn1xlaTLbPhJvnADjg5M5od2dSFC113Oswv/18nK2dzVyoEKKokoAihMg5vQ5OroTtnxmDCbal2FGvO+Njd5Khy6SJVxPmPjMXe0vpCCuEeHISUIQQj6fXwalVhmBy46xhno0LNBvNP14Vmbz3Y7KULNqUbcPnbT7HWiOPphBCPB0JKEKIhzMGk5lwI8wwz8YFmgVB49dZEfEfH4VMRUHheb/n+aTFJ1iqLc1ashCieJCAIoS4n14Hp1cbgknsGcM8G2cIHA1NXgcbJxafWsznBz8HoE/VPrzX9D3UKrX5ahZCFCsSUIQQd+j1cHrVA4JJ0O1g4oyiKMw78g0Ljy8E4NVarzKuwThUKpUZCxdCFDcSUIQQt4PJ6tvBJNQw755gAqBX9Mw8MJPfQ38HYEyDMQytPdRMRQshijMJKEKUZHo9hK6B4M/uBBNrZwgcZQgmti7GVbP0WUzdM5U14WsAeLfJu7xU/SUzFC2EKAkkoAhREun1EPq34a6cmNOGedbOEPgGNBlhEkwAMnWZvLPzHTZd3oRGpeHj5h/TtVLXgq9bCFFiSEARoiTR6+HMWkOLScwpwzxrJ2j6BjQdeV8wAUjLSmPctnHsvrYbS7Uls1rPol25dgVbtxCixJGAIkRJoNfDmXWGFpPok4Z51k6GUNJ0JNiWeuBmSZlJBG0J4nDMYWwtbJnbdi6BPoEFWLgQoqSSgCJEcfagYGLlaAglgW88NJgAxKXHMWLTCELjQnG0cmR+u/nU86xXMHULIUo8CShCFEeKYggmwZ9B9AnDvOxg0nQk2Lk+cvPolGiGbRrGxYSLuNq48t2z31HNtVoBFC6EEAYSUIQoThQFzqyH7Z9C1N3BZIShn8ljgglAZGIkwzYN42ryVbzsvfj+2e+p4Fwhf+sWQoh7SEARojhQFAjbAMEz7gomDoY7cgJH5SiYAJy7dY7hm4ZzI+0G5Z3K8/2z3+Pt4J2PhQshxINJQBGiKFMUCNt4O5gcN8yzcjCMYRIYlONgAnAi9gQjt4wkISOBqqWqsvDZhbjbuudT4UII8WgSUIQoqhKvw5pREL7FMG3lAI2HQ7PRuQomAAeiDhC0JYjUrFTqeNRhfrv5OFs750PRQgiRMxJQhCiKTv8Na8dAWhxY2Ny+K2c02LvlelfbI7czPng8mfpMmng14atnvsLO0i4fihZCiJyTgCJEUZKRBP+8A0d+M0x714We34PHk91hs/HiRt7d+S5ZShZtfNvweevPsdZY52HBQgjxZCSgCFFURO6HlcPg1iVABS3GQpt3wcLqiXa3/OxyPg75GAWFzhU783Hzj7FUW+ZlxUII8cQkoAhR2Om0sGOW4aXowdkXeiyECs2feJeLTi5i9qHZAPSp2of3mr6HWqXOq4qFEOKpSUARojC7GQ4rh8PVg4bpOn3h+Vlg82QdWBVF4Zuj3/Dd8e8AeK3Wa4xtMBaVSpVXFQshRJ6QgCJEYaQocPgX+GcyaFMMgaTzF1C79xPvUq/o+Wz/Zyw5swSAMQ3GMLT20LyqWAgh8pQEFCEKm5Qb8PebELbeMF2hJfRYAM5ln3iXWfospu6ZyprwNQC81+Q9+lXvlxfVCiFEvpCAIkRhcm4TrH4DUmJAbQntphgGXFM/ef+QTF0m7+x8h02XN6FRafi4+cd0rdQ1D4sWQoi8JwFFiMJAmwabpsB+Q98QPKpDrx/Aq/ZT7TZVm8q44HHsubYHS7Uls1rPol25dnlQsBBC5C8JKEKY2/Vj8NcwuBFmmG4yEtp/CJa2T7XbpMwkRm0ZxZGYI9ha2DK37VwCfQLzoGAhhMh/ElCEMBe9DvZ8BVung14LDl7QfT5UfvoWjptpNxm5eSShcaE4Wjkyv9186nnWe/qahRCigEhAEcIc4iNh1Qi4vMswXb0LdP3qiYaqv1dUShTD/hvGpcRLuNq48t2z31HN9clGmhVCCHORgCJEQTu+HNa/BRkJhgf8dfoM6vWHPBiLJCIxgmH/DeNayjW87L34/tnvqeBc4elrFkKIAiYBRYiCkhZvCCYnVximyzaGngvBtWKe7P7srbO8vul1bqTdoLxTeb5/9nu8HbzzZN9CCFHQJKAIURAu7jRc0km8AioNtHkHWowHTd78EzwRe4IRm0eQmJlI1VJVWfjsQtxt3fNk30IIYQ4SUITIT1kZsPUT2PM1oBhaS3p+D2UD8uwQ+6/vZ/TW0aRmpVLHow7z283H2frJhsIXQojCQgKKEPkl5gysHApRJwzTDQZBx/+BtUOe7F5RFNZeWMu0PdPI1GfSxLsJX7X9CjtLuzzZvxBCmJMEFCHymqIYBlzbNAWy0sHODV74Gqp3zrNDRCZF8sneT9hzbQ8AbX3bMqv1LKw11nl2DCGEMCcJKELkpaQow1D14VsM05XbQ7f54Fg6T3afpc/it9O/Me/oPNJ16ViprRhRdwSv1noVC7X8cxZCFB/yP5oQeSV0reEhf2lxYGEDHT6BRkPz5PZhgFM3TzFtzzRC40IBaOzVmCmBUyjvVD5P9i+EEIVJrp9AtmPHDrp27YqPjw8qlYrVq1ebLFcUhSlTpuDt7Y2trS3t27fn3LlzJuvExcXRv39/nJyccHFxYciQISQnJz/VGxHCbDKSYU0QLH3FEE686sDrO6DxsDwJJ6naVGYdmMXL618mNC4UJysnPmr2ET90+EHCiRCi2Mp1QElJSaFu3brMmzfvgctnzpzJV199xYIFC9i3bx/29vZ07NiR9PR04zr9+/fn1KlTbNq0iXXr1rFjxw6GDx/+5O9CCHOJPAALWsCRXwEVtBgHQ7eAR96M3Lrr6i56rOnBL6d/Qa/o6eTXiTXd19CjSg9UedQyI4QQhZFKURTliTdWqVi1ahXdu3cHDK0nPj4+vPXWW0yYMAGAhIQESpcuzaJFi+jXrx+hoaHUqFGDAwcOEBBguNXyn3/+4fnnn+fKlSv4+Pg89riJiYk4OzuTkJCAk5PTk5YvxJPTZcGOWYaXogNnX+ixACq0yJPd30y7ycwDM9lwcQMA3vbevN/0fVqVbZUn+xdCCHPIzed3rltQHuXixYtERUXRvn174zxnZ2eaNGlCSEgIACEhIbi4uBjDCUD79u1Rq9Xs27fvgfvNyMggMTHR5CWE2dwMh586wvZPDeGkdh8YsStPwomiKKw+v5pua7qx4eIG1Co1A2oMYHW31RJOhBAlSp52ko2KigKgdGnTOxZKly5tXBYVFYWnp6dpERYWuLq6Gte514wZM5g2bVpelipE7imK4VLOxndAmwLWztDlC6jdO092H5EYwUchH7EvyhDUq5WqxtRmU6nlXitP9i+EEEVJkbiLZ/LkyYwfP944nZiYiK+vrxkrEiVOyk1Y+yacWWeYrtASun8LLk//e6jVa1l8ajELji0gQ5eBtcaaN+q9wYAaA7BUWz71/oUQoijK04Di5eUFQHR0NN7edx5SFh0dTb169YzrxMTEmGyXlZVFXFyccft7WVtbY20tA1AJMzm3Gda8AcnRoLaEdh9AYBCoNU+96xOxJ5gaMpWzt84C0NS7KVOaTsHXSQK4EKJky9OA4ufnh5eXF1u2bDEGksTERPbt28fIkSMBCAwMJD4+nkOHDtGwYUMAtm7dil6vp0mTJnlZjhBPR5sGmz6E/QsN0x7VDc/R8a7z1LtO0abwzZFv+D30dxQUXKxdmNRoEl0qdpG7c4QQgicIKMnJyZw/f944ffHiRY4ePYqrqyvlypVj7NixfPLJJ1SpUgU/Pz8++OADfHx8jHf6+Pv789xzzzFs2DAWLFiAVqslKCiIfv365egOHiEKxPVj8NcwuBFmmG4yAtpPBUvbp9719sjtfLLvE6JSDH2uulbsyoRGE3C1cX3qfQshRHGR64By8OBB2rZta5zO7hsyaNAgFi1axKRJk0hJSWH48OHEx8fTokUL/vnnH2xsbIzb/P777wQFBdGuXTvUajW9evXiq6++yoO3I8RTykyBfQth2/9ArwWH0tB9vmHI+qd0I+0Gn+7/lH8v/QtAGYcyTGk6hWZlmj31voUQorh5qnFQzEXGQRF5LuokHPoZji+DjNu3sVfvAl2/Anu3p9q1oiisPLeS2Ydmk5SZhEalYWCNgYyoO0KePCyEKFFy8/ldJO7iESJfZKbCqZVwaBFcOXBnfik/aDUR6r381EPVX0y4yEchH3Ew+iAA/q7+TGs2DX83/6farxBCFHcSUETJE30KDma3liQY5qktDC0mAa9ChVagfroxDLU6LT+d/Invjn9Hpj4TWwtbRtUbRX///vLUYSGEyAH5n1KUDJmpcGrV7daS/Xfml6oADQdDvf7g4PmQjXPnaMxRpoVM43y8oTN58zLN+aDpB5RxKJMn+xdCiJJAAooo3qJPG/qWHFt6T2tJZ2j4Kvi1furWkmzJmcnMPTyXpWFLUVBwtXHl7UZv08mvk9w6LIQQuSQBRRQ/2rQ7rSWRdz3fyaX8ndYSx9IP2/qJbI3YyvR904lJNQxC2K1SNyYETMDFxiVPjyOEECWFBBRRfMSEGkLJsT8g/a7WkmrPG4JJxbZ51lpiPGRqDDP2zWBzxGYAfB19+TDwQ5p4y6CDQgjxNCSgiKJNmwan1xg6vUbuvTPfpRw0GAT1XwHHBz9C4WnoFT0rzq5gzqE5JGuTsVBZMLjWYF6v8zo2FjaP34EQQohHkoAiiqaYM3e1lsQb5qk0UK2T4U6cis/keWtJtgvxF5gWMo3DMYcBqO1emw8DP6Saa7V8OZ4QQpREElBE0aFNg9N/Gzq9RoTcme9cDhoOhPoD8qW1JFumLpMfTvzA9ye+J0ufha2FLWMajKFftX5o8uDBgUIIIe6QgCIKv9gwQ2vJ0SX3t5Y0fBUqtc2TJws/yuHow0wNmcrFhIsAtC7bmveavIe3g/djthRCCPEkJKCIwkmbDqF/G/qWROy5M9/Z907fEqf8DweJmYl8eehLlp9dDoCbjRvvNHmHjuU7yq3DQgiRjySgiMIl9uztviVLIO2WYZ5KA1WfM/QtqfRMvreWgOH5OZsjNjNj3wxi02IB6FWlF+MajsPZ2jnfjy+EECWdBBRhflkZd/qWXN59Z75TWWiY3VriU2DlRKVEMX3fdIIjgwGo4FSBKYFTaOTVqMBqEEKIkk4CijCfG+fu9C1JizPMU6kNrSUNX4XK7QqkteRuWy5v4b3d75GiTcFCbcGQWkMYVmcY1hrrAq1DCCFKOgkoomBlZUDoWkMwubTzznynstBgoKG1xLngn1mjV/TMOzqP745/B0AdjzpMC5xG5VKVC7wWIYQQElBEQblxHg4vMrSWpN40zFOpoUpHwyivVZ4t8NaSbEmZSUzeOZntV7YD8Ir/K7wV8JY8dVgIIcxI/gcW+evqIdg8FS7uuDPP0cfQWtJgADiXNVtpABcSLjBm6xguJV7CWmPNh4Ef0rVSV7PWJIQQQgKKyC8ZSbDlY9j/HaAYWksqP2u4E6fys6Ax/6/etohtTN41mRRtCl72XnzZ9ktqutU0d1lCCCGQgCLyQ+g62DARkq4Zpuv0hWc+ABdf89Z1m17Rs/DYQuYfmw9AQOkAPm/9OW62bmauTAghRDYJKCLvJFyFjZPgzDrDdCk/6PKFYeySQiI5M5l3d73LtshtALxc/WUmNJqApdrSzJUJIYS4mwQU8fT0Ojjwg+GSTmYSqC2g2ZvQehJY2pq7OqNLCZd4c9ubXEy4iJXaig8CP6B75e7mLksIIcQDSEARTyfqBKwdY+gMC1C2MXT9EkoXrr4cO67s4O0db5OsTcbTzpMv23xJbY/a5i5LCCHEQ0hAEU8mMwWCP4WQeaDowNoJ2n8IDV8Dtdrc1RnpFT3fH/+eeUfnoaDQwLMBs9vMxt3W3dylCSGEeAQJKCL3zm2G9eMgPsIwXaM7dPoMHL3MWta9UrQpvL/rfTZHbAagb7W+vN3obSw10t9ECCEKOwkoIueSY+Cfd+DkX4ZpZ194/nOo9px563qAiMQIxmwbw/n481iqLXmvyXv0qtrL3GUJIYTIIQko4vH0ejjyC2yaAukJhjFNmoyEtu+CtYO5q7vPrqu7mLRjEkmZSXjYejCn7RzqetQ1d1lCCCFyQQKKeLTYMEMn2IgQw7R3Xeg6F3zqm7euB1AUhR9P/shXh79CQaGuR13mtJmDh52HuUsTQgiRSxJQxINp02HnbNg1B/RasLSHZ96Dxq8XilFg75WqTWXKnin8e+lfAHpV6cW7Td7FSmNl5sqEEEI8icL3SSPM7+IOWDcObp43TFd9ztDXpJCMBHuvyKRIxmwbw7lb57BQWzC58WT6VOtj7rKEEEI8BQko4o7UOPjvfTj6u2Hawctwd06NbqBSmbe2h9hzbQ8Tt08kMTMRNxs35rSdQ33Pwnf5SQghRO5IQBGgKHB8Kfz7LqTeBFQQ8JphXBMbZ3NX90CKorD41GLmHJ6DXtFT2702c9rMobR9aXOXJoQQIg9IQCnpbobD+vFwIdgw7VnD0AnWt7FZy3qUtKw0PtzzIRsvbgSgR+UevNf0Paw11mauTAghRF6RgFJSZWXCnq9gxyzISgcLG8Ozc5q9CYV4ILOryVcZu20sZ+LOYKGyYFLjSfSr1g9VIb0EJYQQ4slIQCmJIvYZbh2ODTVMV2wDXeaAa0WzlvU4+67vY8L2CcRnxONq48rs1rMJ8Aowd1lCCCHygQSUkiQtHrZMg4M/Gabt3KDjDKjTp9B2ggVDf5PfQn9j9sHZ6BQdNdxqMLftXLzsC9fQ+kIIIfKOBJSSQFHg9GrY+DYkRxvm1X8Fnv0Y7FzNWtrjpGelMy1kGusurAPghUov8EHTD7CxsDFzZUIIIfKTBJTiLj4C1k+Ac4YBzHCrAl2/hAotzFpWTlxPvs6YbWMIjQtFo9IwIWAC/f37S38TIQCdTodWqzV3GUKYsLS0RKPR5Mm+JKAUV7os2LcAtk0HbSporKDFeGg5HiwK/90uB6IOMGH7BOLS4yhlXYrPW39OY+/Ce2eREAVFURSioqKIj483dylCPJCLiwteXl5P/cekBJTi6NoRQyfY68cM0+WbQ5cvwaOqWcvKCUVR+OPMH8w6MIssJQt/V3++bPslPg4+5i5NiEIhO5x4enpiZ2cnLYqi0FAUhdTUVGJiYgDw9vZ+qv1JQClOMpINLSb7FoCiBxsX6PAx1HsF1GpzV/dYGboMPg75mDXhawB43u95pjabiq2FrZkrE6Jw0Ol0xnDi5uZm7nKEuI+treH/65iYGDw9PZ/qck+ef2pNnToVlUpl8qpevbpxeXp6OqNGjcLNzQ0HBwd69epFdHR0XpdR8oRthHlNYO98Qzip/SIEHYAGA4tEOIlKiWLwxsGsCV+DWqVmQsAEPm35qYQTIe6S3efEzs7OzJUI8XDZv59P20cqX1pQatasyebNm+8cxOLOYcaNG8f69etZvnw5zs7OBAUF0bNnT3bv3p0fpRR/iddg4yQIXWuYdikPXb6Ayu3NW1cuHI4+zLjgccSlx+Fs7cysVrMI9Ak0d1lCFFpyWUcUZnn1+5kvAcXCwgIvr/vHqEhISODHH39kyZIlPPPMMwD8/PPP+Pv7s3fvXpo2bZof5RRPep1hPJPN0yAzCVQaaDYaWr8NVkXjrytFUVgWtoxP939KlpJF1VJVmdt2LmUdy5q7NCGEEGaWL23/586dw8fHh4oVK9K/f38iIiIAOHToEFqtlvbt7/x1X716dcqVK0dISEh+lFI8RZ2EHzvAhgmGcFKmIby+HZ6dVmTCSaYuk6khU/lk3ydkKVk8V+E5fu30q4QTIYQQQD60oDRp0oRFixZRrVo1rl+/zrRp02jZsiUnT54kKioKKysrXFxcTLYpXbo0UVFRD91nRkYGGRkZxunExMS8LrtoyEyF7Z9ByDegzwIrR2g3BRoNAXXe3HdeEGJSYxgXPI7jscdRq9SMaTCGV2u+Ks3WQhRjbdq0oV69enz55ZfmLkUUEXkeUDp16mT8vk6dOjRp0oTy5cuzbNkyY+/e3JoxYwbTpk3LqxKLpvNbDE8dvnXJMF29Czw/C5yK1u23R2OOMi54HDfSbuBo5cisVrNoXqa5ucsSQohCS6vVYmlZeB/iml/y/fYOFxcXqlatyvnz5/Hy8iIzM/O+AYaio6Mf2Gcl2+TJk0lISDC+IiMj87nqQiQ5Fv4aCr/1NIQTpzLQbwn0+73IhZMVZ1fw6r+vciPtBpVdKvNn5z8lnAhRAgwePJjt27czd+5c492d4eHhDBkyBD8/P2xtbalWrRpz5869b7vu3bszbdo0PDw8cHJyYsSIEWRmZhrXycjI4M0338TT0xMbGxtatGjBgQMHclRXcHAwKpWK9evXU6dOHWxsbGjatCknT540We+vv/6iZs2aWFtbU6FCBWbPnm1c9s0331CrVi3j9OrVq1GpVCxYsMA4r3379rz//vvG6TVr1tCgQQNsbGyoWLEi06ZNIysry7hcpVLx7bff8sILL2Bvb8/06dNz9H6KHSWfJSUlKaVKlVLmzp2rxMfHK5aWlsqKFSuMy8+cOaMASkhISI73mZCQoABKQkJCfpRcOOj1inLoF0WZUU5RPnRSlA+dFWXDJEVJTzR3ZbmWmZWpTNszTam1qJZSa1EtZdy2cUpKZoq5yxKiyElLS1NOnz6tpKWlGefp9XolJUNb4C+9Xp/juuPj45XAwEBl2LBhyvXr15Xr168r6enpypQpU5QDBw4oFy5cUH777TfFzs5OWbp0qXG7QYMGKQ4ODkrfvn2VkydPKuvWrVM8PDyUd99917jOm2++qfj4+CgbNmxQTp06pQwaNEgpVaqUcvPmzcfWtW3bNgVQ/P39lf/++085fvy40qVLF6VChQpKZmamoiiKcvDgQUWtVisfffSREhYWpvz888+Kra2t8vPPPyuKoijHjx9XVCqVEhMToyiKoowdO1Zxd3dX+vbtqyiKomRmZip2dnbKpk2bFEVRlB07dihOTk7KokWLlPDwcOW///5TKlSooEydOtVYF6B4enoqP/30kxIeHq5cvnw5x+e6MHjQ72m23Hx+qxRFUfIy8EyYMIGuXbtSvnx5rl27xocffsjRo0c5ffo0Hh4ejBw5kg0bNrBo0SKcnJwYPXo0AHv27MnxMRITE3F2diYhIQEnJ6e8LL9wyEiCP1+GizsM0161oetcQ2fYIuZq8lUm75zMkZgjqFAxuv5ohtYeKv1NhHgC6enpXLx4ET8/P2xsDA/MTM3MosaUfwu8ltMfdcTOKue9BHLSByUoKIioqChWrFgBGFpQ1q5dS2RkpHFsjQULFjBx4kQSEhJIS0ujVKlSLFq0iJdffhkwXA6pUKECY8eOZeLEiY+sKTg4mLZt2/Lnn3/St29fAOLi4ihbtiyLFi2iT58+9O/fn9jYWP777z/jdpMmTWL9+vWcOnUKRVHw8PBgwYIF9O7dm/r169O3b1/mzp3L9evX2b17N23btiU+Ph47Ozvat29Pu3btmDx5snF/v/32G5MmTeLatWuAoQVl7NixzJkzJ8fntzB50O9pttx8fud5H5QrV67w0ksvcfPmTTw8PGjRogV79+7Fw8MDgDlz5qBWq+nVqxcZGRl07NiR+fPn53UZRZeiwN9vGsKJpR20fReajARN0Rr0N0OXwaKTi/j+xPdk6DJwtHTk01af0qpsK3OXJoQoJObNm8dPP/1EREQEaWlpZGZmUq9ePZN16tatazIwXWBgIMnJyURGRpKQkIBWq6V58zuXii0tLWncuDGhoaE5riMw8M64S66urlSrVs24fWhoKN26dTNZv3nz5nz55ZfodDo0Gg2tWrUiODiY9u3bc/r0ad544w1mzpzJmTNn2L59O40aNTK+h2PHjrF7926TyzY6nY709HRSU1ON6wUEBOS4/uIqzz/1/vzzz0cut7GxYd68ecybNy+vD108HPoZTq0EtQUMWA3lmpi7olzbfXU3/9v3PyKSDLeXN/ZqzJTAKZR3Km/myoQofmwtNZz+qKNZjvs0/vzzTyZMmMDs2bMJDAzE0dGRWbNmsW/fvjyqsOC0adOG7777jp07d1K/fn2cnJyMoWX79u20bt3auG5ycjLTpk2jZ8+e9+3n7tYGe3v7Aqm9MCtaf5YXd9ePw8Z3DN+3n1rkwsn15OvMPDCTzRGGUYQ9bD2YEDCBTn6d5JKOEPlEpVLl6lKLuVhZWaHT6YzTu3fvplmzZrzxxhvGeeHh4fdtd+zYMdLS0ox3ge7duxcHBwd8fX1xd3fHysqK3bt3U7684Q8grVbLgQMHGDt2bI5r27t3L+XKlQPg1q1bnD17Fn9/fwD8/f3vG+l89+7dVK1a1ficmdatWzN27FiWL19OmzZtAENo2bx5M7t37+att94ybtugQQPCwsKoXLlyjusrqQr/b3VJkZ4IyweBLgOqdoLAIHNXlGNanZbFpxfz3fHvSMtKQ6PS0N+/PyPrjsTBysHc5QkhCoEKFSqwb98+Ll26hIODA1WqVOGXX37h33//xc/Pj19//ZUDBw7g5+dnsl1mZiZDhgzh/fff59KlS3z44YcEBQWhVquxt7dn5MiRTJw4EVdXV8qVK8fMmTNJTU1lyJAhOa7to48+ws3NjdKlS/Pee+/h7u5O9+7dAXjrrbdo1KgRH3/8MX379iUkJIRvvvnGpGtCnTp1KFWqFEuWLGHdunWAIaBMmDABlUplcglqypQpdOnShXLlytG7d2/UajXHjh3j5MmTfPLJJ09xhouhPO++WwCK3V08er2iLBtsuFvni5qKkvL43ueFxZ6re5QuK7sY79AZtHGQcjburLnLEqJYetTdEYVdWFiY0rRpU8XW1lYBlDNnziiDBw9WnJ2dFRcXF2XkyJHKO++8o9StW9e4zaBBg5Ru3bopU6ZMUdzc3BQHBwdl2LBhSnp6unGdtLQ0ZfTo0Yq7u7tibW2tNG/eXNm/f3+Oasq+i2ft2rVKzZo1FSsrK6Vx48bKsWPHTNZbsWKFUqNGDcXS0lIpV66cMmvWrPv21a1bN8XCwkJJSkpSFEVRdDqdUqpUKaVp06b3rfvPP/8ozZo1U2xtbRUnJyelcePGynfffWdcDiirVq3K0XsojArtXTwFodjdxXPgR8MgbGoLePUf8G1k7ooeKyolilkHZvHfZUPPdjcbN94KeIsuFbvI5Rwh8smj7o4ojgYPHkx8fDyrV6/Ol/1n38Vz69at+0Y4F0+u0N7FI3Lp+jH45/btZu2nFfpwotVp+S30N7499i1pWWmoVWpeqv4So+qNwtHK0dzlCSGEKCYkoJhTeiIsu7vfyShzV/RI+6/vZ/q+6VxIuABAPY96vN/0faq5VjNzZUIIcb8RI0bw22+/PXDZK6+8Qr9+/Qq4IpEbElDMRVFg7Ztw6yI4+0L3+VBIL43EpMbw+cHP2XhxIwCuNq6MbzierpW6olbl+9MShBAl1KJFi55q+48++ogJEyY8cJmTkxOenp4UwV4OJYYEFHM5+COcWmXod9L7Z7BzNXdF99HqtSwJXcL8o/NJzUpFrVLTp2ofguoH4WztbO7yhBDikTw9PfH09DR3GeIJSUAxh2tH7/Q7efajQtnv5GDUQabvm875+PMA1HGvw3tN36OGWw0zVyaEEKIkkIBS0NITYPlg0GVCteeh6RuP3aQg3Ui7weyDs1l3wXAvv4u1C+MajqN75e5yOUcIIUSBkYBSkLKfs3PrIjiXg27zCk2/kyx9FkvDlvLNkW9I1iajQsWLVV/kzQZvyuUcIYQQBU4CSkE68AOcXg1qS3ix8PQ7ORJzhE/2fsLZW2cBqOlWk/ebvk8t91pmrkwIIURJJQGloFw7Av++a/j+2Y+grPmfVHkz7SZzDs1hTfgaAJysnBjTYAy9qvRCo366B4EJIYQQT0MCSkEw6XfSGZqONGs5Or2OZWeX8fWRr0nKTAKgV5VejGkwhlI2pcxamxBC5MbUqVNZvXo1R48eNXcpIo9JQMlvigJ/j4Zbl8ClHHQ3b7+TY7HHmL53OqFxoQD4u/rzXtP3qOtR12w1CSGEEPeSgJLf9n8Pp9cY+p30XgS25mmhiEuPY+7huaw8txIARytH3qz/Ji9WfVEu5wghClxmZiZWVlbmLqPQ0el0qFQq1Gq5a1LOQH66ehj+e8/wfYePoWzDAi9Bp9exLGwZXVd1NYaTbpW6sbb7WvpV7yfhRAhRINq0aUNQUBBjx47F3d2djh078sUXX1C7dm3s7e3x9fXljTfeIDk52bjNokWLcHFxYfXq1VSpUgUbGxs6duxIZGTkE9UwePBgunfvzrRp0/Dw8MDJyYkRI0aQmZlpXCcjI4M333wTT09PbGxsaNGiBQcOHDAuDwgI4PPPPzdOd+/eHUtLS2PdV65cQaVScf78eeP+JkyYQJkyZbC3t6dJkyYEBwff9x7//vtvatSogbW1NREREU/0/oobCSj5JS3+Tr+T6l2gyYgCL+HkjZP039Cfj/d+TGJmItVKVeOXTr/wSYtPcLN1K/B6hBD5QFEgM6XgX08wRPzixYuxsrJi9+7dLFiwALVazVdffcWpU6dYvHgxW7duZdKkSSbbpKamMn36dH755Rd2795NfHz8Uz1DZ8uWLYSGhhIcHMwff/zBypUrmTZtmnH5pEmT+Ouvv1i8eDGHDx+mcuXKdOzYkbi4OABat25tDBiKorBz505cXFzYtWsXANu3b6dMmTJUrlwZgKCgIEJCQvjzzz85fvw4L774Is899xznzp0zeY+fffYZP/zwA6dOnZLRb2+TSzz5QVHg7yCIv2zod9LtmwLtdxKfHs9XR75ixdkVKCg4WDoQVD+IvtX6YqGWH7kQxYo2Ff7nU/DHffcaWNnnapMqVaowc+ZM43S1anceNFqhQgU++eQTRowYwfz5843ztVot33zzDU2aNAEMIcff35/9+/fTuHHjXJdtZWXFTz/9hJ2dHTVr1uSjjz5i4sSJfPzxx6SlpfHtt9+yaNEiOnXqBMD333/Ppk2b+PHHH5k4cSJt2rThxx9/RKfTcfLkSaysrOjbty/BwcE899xzBAcH07p1awAiIiL4+eefiYiIwMfH8DOaMGEC//zzDz///DP/+9//jO9x/vz51K0rfQHvJp9W+WH/dxC69vZ4J4sKrN+JXtGz6twqvjz8JfEZ8QB0rdiV8QHjcbd1L5AahBDiYRo2NL3MvXnzZmbMmMGZM2dITEwkKyuL9PR0UlNTsbOzA8DCwoJGje48DqR69eq4uLgQGhr6RAGlbt26xn0DBAYGkpycTGRkJAkJCWi1Wpo3b25cbmlpSePGjQkNNdxY0LJlS5KSkjhy5Ah79uyhdevWtGnThk8//RQwtKBMnDgRgBMnTqDT6ahatapJDRkZGbi53WnFtrKyok6dOrl+L8WdBJS8dvUw/Jvd7+QTKFMw/U5O3zzN9L3TOX7jOACVXSrzXpP3CPAy/3grQoh8ZGlnaM0wx3Fzyd7+TovLpUuX6NKlCyNHjmT69Om4urqya9cuhgwZQmZmpkmIKExcXFyoW7cuwcHBhISE8Oyzz9KqVSv69u3L2bNnOXfunLEFJTk5GY1Gw6FDh9BoTPv7OTg4GL+3tbVFVUhGFS9MJKDkpex+J3rt7X4nr+f7IRMyEvj6yNcsC1uGgoK9pT1v1H2Dl/xfwlJtme/HF0KYmUqV60sthcGhQ4fQ6/XMnj3beMfKsmXL7lsvKyuLgwcPGltLwsLCiI+Px9/f/4mOe+zYMdLS0rC1tQVg7969ODg44Ovri7u7u7GPTPny5QHD5ZcDBw4wduxY4z5at27Ntm3b2L9/vzFc+fv7M336dLy9vY0tJvXr10en0xETE0PLli2fqN6STDrJ5hVFgTWjbvc7KZ/vz9nRK3pWn1/NC6tfYGnYUhQUnvd7nr+7/83AmgMlnAghCrXKlSuj1Wr5+uuvuXDhAr/++isLFiy4bz1LS0tGjx7Nvn37OHToEIMHD6Zp06ZPdHkHDLc3DxkyhNOnT7NhwwY+/PBDgoKCUKvV2NvbM3LkSCZOnMg///zD6dOnGTZsGKmpqQwZMsS4jzZt2vDvv/9iYWFB9erVjfN+//13Y+sJQNWqVenfvz8DBw5k5cqVXLx4kf379zNjxgzWr1//RPWXJNKCklf2LYQz6+7qd+KSb4c6E3eG6XunczT2KAAVnSvyXpP3aOz9ZP9ghRCioNWtW5cvvviCzz77jMmTJ9OqVStmzJjBwIEDTdazs7Pj7bff5uWXX+bq1au0bNmSH3/88YmP265dO6pUqUKrVq3IyMjgpZdeYurUqcbln376KXq9ngEDBpCUlERAQAD//vsvpUrd6UvYsmVL9Hq9SRhp06YNc+fOpU2bNibH+/nnn/nkk0946623uHr1Ku7u7jRt2pQuXbo88XsoKVSK8gT3iplZYmIizs7OJCQk4OTkZO5y4Ooh+LGj4dJOp5n5dmknKTOJb458w59hf6JX9Nha2PJG3Tfo798fS420mAhR3KWnp3Px4kX8/PywsbExdzn5btGiRYwdO5b4+Pg82d/gwYOJj49n9erVebI/8WCP+j3Nzee3tKA8rbRbd/qd+L8AjYfn+SEURWHdhXXMPjibm+k3AehYoSMTAibgZe+V58cTQgghzE0CytNQFFgTBPERUKpCvox3cvbWWabvnc7hmMMAVHCqwLtN3iXQJzBPjyOEEEXd3XfG3Gvjxo0FWInICxJQnsa+BYZ+JxorQ78TG+c823VyZjLzj81nSegSdIoOWwtbhtcZzqAag+RyjhCiRBg8eDCDBw/O8fqPeqJxmTJl5E6aIkYCypO6cgj++8DwfYfp4FM/T3YbmRTJynMrWXluJXHphqGVny3/LBMDJuLt4J0nxxBCiOIoe3h5UTxIQHkSd/c7qdENGg97qt1pdVq2RG7hr7N/sff6XuP8co7lmNxkMi3KtHjKgoUQQoiiRQJKbikKrB4FCbf7nbzw9RP3O7mUcIm/zv3F3+F/G1tLVKhoVqYZvav0prVvaxnPRAghRIkkASW39n4LYeufuN9Jhi6DzZc3s+LsCg5GHzTO97T1pEeVHvSo0oMyDmXyuGghhBCiaJGAkhtXDsKm2/1OOv4vV/1OwuPDWXF2BWsvrCUhIwEAtUpNyzIt6V21Ny3KtJAnDQshhBC3ySdiTqXGwfJXQZ8FNbpDo6GP3SQ9K53/Lv/HirMrOBJzxDjfy96LnlV60qNyDxnHRAghhHgACSg5kf2cnYQIKOUHL3z1yH4nYXFh/HXuL9ZdWEdSZhIAGpWG1mVb07tqb5r5NEOj1jx0eyGEEI9WFEeFLYo1m5MElJzYOx/CNjyy30mqNpV/L/3LirMrOH7juHF+GYcy9KrSi+6Vu+Nh51GARQshRNF36dIl/Pz8OHLkCPXq1TPOnzt3LgXxpBYJFeYjAeVxIg/ApimG7zv+D3zqmSw+ffM0f539i/UX15OiTQHAQmVB23Jt6V21N029m6JWyUOjhRAiLzk7593AmOLJZGZmYmVllW/7l0/OR0mNgxW3+53U7GHsd5KcmcyysGX0XdeXvuv6suzsMlK0KZRzLMe4huPY9OImvmjzBc18mkk4EUIIQK/XM2PGDPz8/LC1taVu3bqsWLECgFu3btG/f388PDywtbWlSpUq/PzzzwD4+fkBUL9+fVQqlfFpwYMHD6Z79+7G/bdp04bRo0czduxYSpUqRenSpfn+++9JSUnh1VdfxdHRkcqVK5sMea/T6RgyZIixpmrVqjF37lzj8qlTp7J48WLWrFmDSqVCpVIRHBwMQGRkJH369MHFxQVXV1e6devGpUuXTPY9fvx4XFxccHNzY9KkSblq8WnTpg1BQUEEBQXh7OyMu7s7H3zwgck+bt26xcCBAylVqhR2dnZ06tSJc+fOAYZnuHl4eBjPMUC9evXw9r4z4OeuXbuwtrYmNTUVgPj4eIYOHYqHhwdOTk4888wzHDt2zOR81KtXjx9++KFAHlgpLSgPoyiw+g1IiIRSfihd5nLyxkn+OvcXGy5uIC0rDQBLtSXty7end5XeNPJqhCqPn8UjhBCPoiiK8f+jgmRrYZur/+9mzJjBb7/9xoIFC6hSpQo7duzglVdewcPDg+XLl3P69Gk2btyIu7s758+fJy3N8J72799P48aN2bx5MzVr1nzkX+yLFy9m0qRJ7N+/n6VLlzJy5EhWrVpFjx49ePfdd5kzZw4DBgwgIiICOzs79Ho9ZcuWZfny5bi5ubFnzx6GDx+Ot7c3ffr0YcKECYSGhpKYmGgMTK6urmi1Wjp27EhgYCA7d+7EwsKCTz75hOeee47jx49jZWXF7NmzWbRoET/99BP+/v7Mnj2bVatW8cwzz+T4nC1evJghQ4awf/9+Dh48yPDhwylXrhzDhhkGBx08eDDnzp3j77//xsnJibfffpvnn3+e06dPY2lpSatWrQgODqZ3797cunWL0NBQbG1tOXPmDNWrV2f79u00atQIOzs7AF588UVsbW3ZuHEjzs7OLFy4kHbt2nH27FlcXV0BOH/+PH/99RcrV65Eo8nfvpQSUB4m5Bs4u5FEC2vWN32FvzYNIexWmHGxn7Mfvar04oVKL1DKppQZCxVClGRpWWk0WdKkwI+77+V92Fna5WjdjIwM/ve//7F582YCAw0POq1YsSK7du1i4cKFJCcnU79+fQICAgCoUKGCcVsPD0PfPTc3N7y8Hn3XY926dXn//fcBmDx5Mp9++inu7u7GD/QpU6bw7bffcvz4cZo2bYqlpSXTpk0zbu/n50dISAjLli2jT58+ODg4YGtrS0ZGhsmxf/vtN/R6PT/88IMxpP3888+4uLgQHBxMhw4d+PLLL5k8eTI9e/YEYMGCBfz77785Ol/ZfH19mTNnDiqVimrVqnHixAnmzJnDsGHDjMFk9+7dNGvWDIDff/8dX19fVq9ezYsvvkibNm1YuHAhADt27KB+/fp4eXkRHBxM9erVCQ4OpnXr1oChNWX//v3ExMRgbW0NwOeff87q1atZsWIFw4cPBwyXdX755RfjzyU/SUB5ACViH8d2TmeFuyv/OrmQfmYxANYaazqU70Cvqr1o4NlAWkuEECIHzp8/T2pqKs8++6zJ/MzMTOrXr8/UqVPp1asXhw8fpkOHDnTv3t34oZsbderUMX6v0Whwc3Ojdu3axnmlS5cGICYmxjhv3rx5/PTTT0RERJCWlkZmZqZJZ9wHOXbsGOfPn8fR0dFkfnp6OuHh4SQkJHD9+nWaNLkTHC0sLAgICMjVZZ6mTZuafM4EBgYye/ZsdDodoaGhWFhYmBzDzc2NatWqERoaCkDr1q0ZM2YMsbGxbN++nTZt2hgDypAhQ9izZw+TJk0yvqfk5GTc3NxMakhLSyM8PNw4Xb58+QIJJ2DmgDJv3jxmzZpFVFQUdevW5euvv6Zx48ZmqychI4G1Z5by18GvOO91+wegZFHZpTK9q/amS8UuOFtLxywhROFha2HLvpf3meW4OZWcnAzA+vXrKVPGdKRsa2trfH19uXz5Mhs2bGDTpk20a9eOUaNG8fnnn+eqJktL00eDqFQqk3nZH/Z6vR6AP//8kwkTJjB79mwCAwNxdHRk1qxZ7Nv36POZnJxMw4YN+f333+9bVlAf3jlRu3ZtXF1d2b59O9u3b2f69Ol4eXnx2WefceDAAbRarTEIJicn4+3tbexjczcXFxfj9/b29gVUvRkDytKlSxk/fjwLFiygSZMmfPnll3Ts2JGwsDA8PT3NUtNPJ37ip1M/gYUKGwWeq9iZ3v4vUce9jrSWCCEKJZVKleNLLeZSo0YNrK2tiYiIMF5SuJeHhweDBg1i0KBBtGzZkokTJ/L5558b+5zodLo8ryv78sgbb7xhnHd3awGAlZXVfcdu0KABS5cuxdPTEycnpwfu29vbm3379tGqVSsAsrKyOHToEA0aNMhxffcGpb1791KlShU0Gg3+/v5kZWWxb98+Y8i4efMmYWFh1KhRAzD8brRs2ZI1a9Zw6tQpWrRogZ2dHRkZGSxcuJCAgABj4GjQoAFRUVFYWFiYXGIzJ7PdYvLFF18wbNgwXn31VWrUqMGCBQuws7Pjp59+MldJ9EpKxj8jk/fjEtn6zHd83OpT6nrUlXAihBBPwdHRkQkTJjBu3DgWL15MeHg4hw8f5uuvv2bx4sVMmTKFNWvWcP78eU6dOsW6devw9/cHwNPTE1tbW/755x+io6NJSEjIs7qqVKnCwYMH+ffffzl79iwffPABBw4cMFmnQoUKHD9+nLCwMG7cuIFWq6V///64u7vTrVs3du7cycWLFwkODubNN9/kypUrAIwZM4ZPP/2U1atXc+bMGd544w3i4+NzVV9ERATjx48nLCyMP/74g6+//poxY8YYa+/WrRvDhg1j165dHDt2jFdeeYUyZcrQrVs34z7atGnDH3/8Qb169XBwcECtVtOqVSt+//13k7DYvn17AgMD6d69O//99x+XLl1iz549vPfeexw8ePC+2gqCWQJKZmYmhw4don379ncKUatp3749ISEh962fkZFBYmKiySs/lPN7hmVJKvq2mIJjucB8OYYQQpREH3/8MR988AEzZszA39+f5557jvXr1+Pn54eVlRWTJ0+mTp06tGrVCo1Gw59//gkY+m589dVXLFy4EB8fH5MP36f1+uuv07NnT/r27UuTJk24efOmSWsKwLBhw6hWrRoBAQF4eHiwe/du7Ozs2LFjB+XKlaNnz574+/szZMgQ0tPTjS0qb731FgMGDGDQoEHGy0c9evTIVX0DBw4kLS2Nxo0bM2rUKMaMGWPsrAqGjrkNGzakS5cuBAYGoigKGzZsMLms1bp1a3Q6nfH2bDCElnvnqVQqNmzYQKtWrXj11VepWrUq/fr14/Lly8a+OwVNpRTEUHz3uHbtGmXKlGHPnj3GHt0AkyZNYvv27fc1a02dOtWkp3W2hISEhzavPbH0BLB2euRQ9kIIYQ7p6elcvHixQMagEObVpk0b6tWrx5dffmnuUnLtUb+niYmJODs75+jzu0iMIjZ58mQSEhKMr8jIyPw7mI2zhBMhhBDCzMzSSdbd3R2NRkN0dLTJ/Ojo6Afe525tbW28L1sIIYQoyiIiIowdWR/k9OnTBVhN4WWWgGJlZUXDhg3ZsmWLcahivV7Pli1bCAoKMkdJQgghRIHw8fHh6NGjj1z+oNt9Sxqz3WY8fvx4Bg0aREBAAI0bN+bLL780PjNBCCGEKK4sLCyoXLmyucso9MwWUPr27UtsbCxTpkwhKiqKevXq8c8//5itt7AQQgghCg+zjiSb/aRGIYQQOWeGmy+FyLG8+v0sEnfxCCGEuDOUe2pqqpkrEeLhsn8/7330QG7JwwKFEKKI0Gg0uLi4GB92Z2dnJyNdi0JDURRSU1OJiYnBxcUFjUbzVPuTgCKEEEVI9lAMdz+RV4jCxMXF5YFDhuSWBBQhhChCVCoV3t7eeHp6otVqzV2OECYsLS2fuuUkmwQUIYQogjQaTZ59EAhRGEknWSGEEEIUOhJQhBBCCFHoSEARQgghRKFTJPugZA8Ck5iYaOZKhBBCCJFT2Z/bORnMrUgGlKSkJAB8fX3NXIkQQgghcispKQlnZ+dHrqNSiuCYyXq9nmvXruHo6CiDFBWgxMREfH19iYyMxMnJydzllChy7s1Hzr35yLk3n/w694qikJSUhI+PD2r1o3uZFMkWFLVaTdmyZc1dRonl5OQk/1mYiZx785Fzbz5y7s0nP87941pOskknWSGEEEIUOhJQhBBCCFHoSEAROWZtbc2HH36ItbW1uUspceTcm4+ce/ORc28+heHcF8lOskIIIYQo3qQFRQghhBCFjgQUIYQQQhQ6ElCEEEIIUehIQBFCCCFEoSMBRZiYMWMGjRo1wtHREU9PT7p3705YWJjJOunp6YwaNQo3NzccHBzo1asX0dHRZqq4+Pr0009RqVSMHTvWOE/Off65evUqr7zyCm5ubtja2lK7dm0OHjxoXK4oClOmTMHb2xtbW1vat2/PuXPnzFhx8aDT6fjggw/w8/PD1taWSpUq8fHHH5s8q0XOfd7YsWMHXbt2xcfHB5VKxerVq02W5+Q8x8XF0b9/f5ycnHBxcWHIkCEkJyfnS70SUISJ7du3M2rUKPbu3cumTZvQarV06NCBlJQU4zrjxo1j7dq1LF++nO3bt3Pt2jV69uxpxqqLnwMHDrBw4ULq1KljMl/Off64desWzZs3x9LSko0bN3L69Glmz55NqVKljOvMnDmTr776igULFrBv3z7s7e3p2LEj6enpZqy86Pvss8/49ttv+eabbwgNDeWzzz5j5syZfP3118Z15NznjZSUFOrWrcu8efMeuDwn57l///6cOnWKTZs2sW7dOnbs2MHw4cPzp2BFiEeIiYlRAGX79u2KoihKfHy8YmlpqSxfvty4TmhoqAIoISEh5iqzWElKSlKqVKmibNq0SWndurUyZswYRVHk3Oent99+W2nRosVDl+v1esXLy0uZNWuWcV58fLxibW2t/PHHHwVRYrHVuXNn5bXXXjOZ17NnT6V///6Kosi5zy+AsmrVKuN0Ts7z6dOnFUA5cOCAcZ2NGzcqKpVKuXr1ap7XKC0o4pESEhIAcHV1BeDQoUNotVrat29vXKd69eqUK1eOkJAQs9RY3IwaNYrOnTubnGOQc5+f/v77bwICAnjxxRfx9PSkfv36fP/998blFy9eJCoqyuTcOzs706RJEzn3T6lZs2Zs2bKFs2fPAnDs2DF27dpFp06dADn3BSUn5zkkJAQXFxcCAgKM67Rv3x61Ws2+ffvyvKYi+bBAUTD0ej1jx46lefPm1KpVC4CoqCisrKxwcXExWbd06dJERUWZocri5c8//+Tw4cMcOHDgvmVy7vPPhQsX+Pbbbxk/fjzvvvsuBw4c4M0338TKyopBgwYZz2/p0qVNtpNz//TeeecdEhMTqV69OhqNBp1Ox/Tp0+nfvz+AnPsCkpPzHBUVhaenp8lyCwsLXF1d8+VnIQFFPNSoUaM4efIku3btMncpJUJkZCRjxoxh06ZN2NjYmLucEkWv1xMQEMD//vc/AOrXr8/JkydZsGABgwYNMnN1xduyZcv4/fffWbJkCTVr1uTo0aOMHTsWHx8fOfclnFziEQ8UFBTEunXr2LZtG2XLljXO9/LyIjMzk/j4eJP1o6Oj8fLyKuAqi5dDhw4RExNDgwYNsLCwwMLCgu3bt/PVV19hYWFB6dKl5dznE29vb2rUqGEyz9/fn4iICADj+b33jik5909v4sSJvPPOO/Tr14/atWszYMAAxo0bx4wZMwA59wUlJ+fZy8uLmJgYk+VZWVnExcXly89CAoow8f/27iWmiTUMA/ALAoWmXIwYEEhJkRpBEjAUm7FLFhrjJa4MYYGXjRIjC1OIIoEYS+q1YaELWJSFEHRhNWJ0Q9VE1BpIGwwQZMFlIQtDNCWCiPQ7ixMnjsoJQXqYw3mfZJJ25puZr/+ivOn8M4gITp8+DZ/PB7/fD4vFotleWlqK+Ph49PT0qOtGRkYwOTkJRVH+7XbXlfLycrx9+xahUEhdbDYbKisr1dcc++hwOBy/3E7/7t075ObmAgAsFgsyMzM1Yx8OhxEIBDj2f2h2dhaxsdo/RRs2bEAkEgHAsf+3LGecFUXBp0+f0N/fr9b4/X5EIhHY7fbVb2rVp93Sf9qpU6ckNTVVnj17JlNTU+oyOzur1pw8eVLMZrP4/X7p6+sTRVFEUZQ17Hr9+vEuHhGOfbS8efNG4uLixOVyyejoqHR0dIjRaJTbt2+rNW63W9LS0uTBgwcyMDAghw4dEovFInNzc2vY+X9fVVWVZGdnS3d3t4yNjcm9e/ckPT1damtr1RqO/eqYmZmRYDAowWBQAMiNGzckGAzKxMSEiCxvnPfu3Ss7d+6UQCAgL168EKvVKhUVFVHplwGFNAD8dvF6vWrN3NycVFdXy8aNG8VoNMrhw4dlampq7Zpex34OKBz76Hn48KEUFRWJwWCQ7du3S2trq2Z7JBKRhoYGycjIEIPBIOXl5TIyMrJG3a4f4XBYampqxGw2S2JiouTl5Ul9fb3Mz8+rNRz71fH06dPffr9XVVWJyPLGeXp6WioqKsRkMklKSoocO3ZMZmZmotJvjMgPj+sjIiIi0gHOQSEiIiLdYUAhIiIi3WFAISIiIt1hQCEiIiLdYUAhIiIi3WFAISIiIt1hQCEiIiLdYUAhIt1qampCSUnJujkPES0fAwoRERHpDgMKERER6Q4DChH9o0gkgitXriA/Px8GgwFmsxkulwvj4+OIiYlBV1cXdu/ejcTERBQVFeH58+fqvu3t7UhLS9Mc7/79+4iJiVlxLxcvXkROTg4MBgNKSkrw5MkTTU1dXR22bdsGo9GIvLw8NDQ0YGFhQVPjdruRkZGB5ORknDhxAl++fFlRP0QUPQwoRPSPzp07B7fbjYaGBgwNDaGzsxMZGRnqdqfTibNnzyIYDEJRFBw4cADT09NR6aWlpQXXr1/HtWvXMDAwgD179uDgwYMYHR1Va5KTk9He3o6hoSG0tLSgra0NHo9H3X737l00NTWhubkZfX192LJlC27duhWVfonoD0TlXxAS0boQDofFYDBIW1vbL9vGxsYEgLjdbnXdwsKC5OTkyOXLl0VExOv1SmpqqmY/n88ny/3qaWxslOLiYvV9VlaWuFwuTU1ZWZlUV1cveYyrV69KaWmp+l5RlF/q7Xa75jxEtPb4CwoRLWl4eBjz8/MoLy9fskZRFPV1XFwcbDYbhoeHV72XcDiM9+/fw+FwaNY7HA7N+e7cuQOHw4HMzEyYTCZcuHABk5OT6vbh4WHY7fYlPwMR6QMDChEtKSkp6Y/2j42NhYho1v08H2Q1vXr1CpWVldi3bx+6u7sRDAZRX1+Pr1+/Ru2cRBQdDChEtCSr1YqkpCT09PQsWfP69Wv19bdv39Df34+CggIAwObNmzEzM4PPnz+rNaFQaEW9pKSkICsrC729vZr1vb29KCwsBAC8fPkSubm5qK+vh81mg9VqxcTEhKa+oKAAgUBgyc9ARPoQt9YNEJF+JSYmoq6uDrW1tUhISIDD4cCHDx8wODioXva5efMmrFYrCgoK4PF48PHjRxw/fhwAYLfbYTQacf78eZw5cwaBQADt7e0r7sfpdKKxsRFbt25FSUkJvF4vQqEQOjo6APwdqCYnJ9HV1YWysjI8evQIPp9Pc4yamhocPXoUNpsNDocDHR0dGBwcRF5e3or7IqIoWOtJMESkb4uLi3Lp0iXJzc2V+Ph4MZvN0tzcrE6S7ezslF27dklCQoIUFhaK3+/X7O/z+SQ/P1+SkpJk//790trauuJJsouLi9LU1CTZ2dkSHx8vxcXF8vjxY80+TqdTNm3aJCaTSY4cOSIej+eXiboul0vS09PFZDJJVVWV1NbWcpIskc7EiPx0gZiIaBnGx8dhsVgQDAb5mHgiWnWcg0JERES6w4BCRGtmx44dMJlMv12+zyshov8nXuIhojUzMTGx5G3H3x9FT0T/TwwoREREpDu8xENERES6w4BCREREusOAQkRERLrDgEJERES6w4BCREREusOAQkRERLrDgEJERES6w4BCREREuvMXEJHougZ/L1wAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plot(df_some_cores,with_tapo=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Intel(R) Xeon(R) CPU E3-1240 V2 @ 3.40GHz"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's a 4 cores, 8 threads CPU with a TDP of 69W, according to https://www.intel.com/content/www/us/en/products/sku/65730/intel-xeon-processor-e31240-v2-8m-cache-3-40-ghz/specifications.html, and that's what we have in codeCarbon database.\n",
    "\n",
    "`lscpu` report a max frequency of 3.8 GHz, for a base of 3.4 GHz.\n",
    "\n",
    "On this machine, RAPL report one `core` and one `package`, but no `dram`.\n",
    "\n",
    "When using stress-ng to stress the CPU, we see:\n",
    "    \n",
    "```bash\n",
    "stress-ng --cpu 0 --cpu-method matrixprod --metrics-brief --rapl --perf -t 60s\n",
    "...\n",
    "stress-ng: info:  [6722]  core                   43.31 W\n",
    "stress-ng: info:  [6722]  pkg-0                  47.26 W\n",
    "...\n",
    "```\n",
    "\n",
    "So here `core` seems to be included in `package`, that were not the case for the AMD Threadripper.\n",
    "\n",
    "So we must not update CodeCarbon to include the `core` in the energy measurement of the `package`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cores_used</th>\n",
       "      <th>cpu_load</th>\n",
       "      <th>temperature</th>\n",
       "      <th>cpu_freq</th>\n",
       "      <th>rapl_power</th>\n",
       "      <th>estimated_power</th>\n",
       "      <th>tapo_power</th>\n",
       "      <th>tapo_energy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>49.0</td>\n",
       "      <td>1599.327875</td>\n",
       "      <td>0.176279</td>\n",
       "      <td>0.905903</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>12.5</td>\n",
       "      <td>49.8</td>\n",
       "      <td>1599.292875</td>\n",
       "      <td>5.508811</td>\n",
       "      <td>7.701290</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>21.8</td>\n",
       "      <td>49.8</td>\n",
       "      <td>1615.887000</td>\n",
       "      <td>6.874428</td>\n",
       "      <td>14.458839</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>32.5</td>\n",
       "      <td>51.2</td>\n",
       "      <td>1608.707625</td>\n",
       "      <td>8.150963</td>\n",
       "      <td>21.122903</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>41.2</td>\n",
       "      <td>52.6</td>\n",
       "      <td>1774.674000</td>\n",
       "      <td>9.590357</td>\n",
       "      <td>27.519871</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8</td>\n",
       "      <td>51.3</td>\n",
       "      <td>67.0</td>\n",
       "      <td>3691.394500</td>\n",
       "      <td>14.386126</td>\n",
       "      <td>34.119387</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8</td>\n",
       "      <td>60.8</td>\n",
       "      <td>67.8</td>\n",
       "      <td>3203.470375</td>\n",
       "      <td>24.131781</td>\n",
       "      <td>40.801258</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>71.3</td>\n",
       "      <td>82.6</td>\n",
       "      <td>3592.053000</td>\n",
       "      <td>29.980918</td>\n",
       "      <td>47.273903</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>80.2</td>\n",
       "      <td>86.0</td>\n",
       "      <td>3594.703500</td>\n",
       "      <td>44.586925</td>\n",
       "      <td>53.581839</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8</td>\n",
       "      <td>88.9</td>\n",
       "      <td>84.6</td>\n",
       "      <td>3591.723000</td>\n",
       "      <td>47.199718</td>\n",
       "      <td>60.172452</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8</td>\n",
       "      <td>100.0</td>\n",
       "      <td>85.2</td>\n",
       "      <td>3591.759875</td>\n",
       "      <td>48.402222</td>\n",
       "      <td>66.440323</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cores_used  cpu_load  temperature     cpu_freq  rapl_power  \\\n",
       "0            8       2.5         49.0  1599.327875    0.176279   \n",
       "1            8      12.5         49.8  1599.292875    5.508811   \n",
       "2            8      21.8         49.8  1615.887000    6.874428   \n",
       "3            8      32.5         51.2  1608.707625    8.150963   \n",
       "4            8      41.2         52.6  1774.674000    9.590357   \n",
       "5            8      51.3         67.0  3691.394500   14.386126   \n",
       "6            8      60.8         67.8  3203.470375   24.131781   \n",
       "7            8      71.3         82.6  3592.053000   29.980918   \n",
       "8            8      80.2         86.0  3594.703500   44.586925   \n",
       "9            8      88.9         84.6  3591.723000   47.199718   \n",
       "10           8     100.0         85.2  3591.759875   48.402222   \n",
       "\n",
       "    estimated_power  tapo_power  tapo_energy  \n",
       "0          0.905903           0            0  \n",
       "1          7.701290           0            0  \n",
       "2         14.458839           0            0  \n",
       "3         21.122903           0            0  \n",
       "4         27.519871           0            0  \n",
       "5         34.119387           0            0  \n",
       "6         40.801258           0            0  \n",
       "7         47.273903           0            0  \n",
       "8         53.581839           0            0  \n",
       "9         60.172452           0            0  \n",
       "10        66.440323           0            0  "
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv = '../codecarbon/data/hardware/cpu_load_profiling/E3-1240/compare_cpu_load_and_RAPL-all_cores-Intel(R)_Xeon(R)_CPU_E3-1240_V2_@_3.40GHz-2025-01-14.csv'\n",
    "df_all_cores = get_df(csv)\n",
    "display_df(df_all_cores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'CPU Load vs Power Consumption'}, xlabel='cpu_load'>"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(df_all_cores)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'CPU Load vs Power Consumption'}, xlabel='cpu_load'>"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAh8AAAHHCAYAAAAf2DoOAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQAAdYJJREFUeJzt3Xd4FNXbxvHvpveEFJIASQg99B4iIKgooihIERQFFPBVqaKg2BAVwYroT0UsgArSFEQQUECqdKX3DgKhJoH0ZM/7x8JqpEgwZFPuz3XlkjM7M/vszpq9M3PmHIsxxiAiIiKST5wcXYCIiIgULwofIiIikq8UPkRERCRfKXyIiIhIvlL4EBERkXyl8CEiIiL5SuFDRERE8pXCh4iIiOQrhQ8RERHJVwofIg504MABLBYL48ePd3QpItdMn1v5rxQ+5Ibau3cv//d//0e5cuXw8PDAz8+Pxo0bM3r0aFJTU+3rlS1bFovFYv8pWbIkTZs2ZcaMGTn2V7ZsWVq3bn3Z51q3bt01/UJcvHgxFouF6dOn/+fXV1SMHz8+x/vv4eFBpUqV6NOnD/Hx8Y4uL8/MmDGDVq1aERwcjJubG6VKleL+++9n0aJFji6tQJo0aRLvv/++o8uQIsjF0QVI0TVnzhw6duyIu7s7Xbt2pXr16mRkZLB8+XIGDRrE1q1bGTt2rH392rVr8/TTTwNw9OhRPv30U9q1a8cnn3zC448/7qiXUay8+uqrREdHk5aWxvLly/nkk0/46aef2LJlC15eXo4u77oZY3j00UcZP348derUYeDAgYSFhXHs2DFmzJjBbbfdxooVK7jpppscXWqBMmnSJLZs2cKAAQNyLI+KiiI1NRVXV1fHFCaFnsKH3BD79++nc+fOREVFsWjRIsLDw+2P9e7dmz179jBnzpwc25QuXZqHHnrI3u7atSsVKlRg1KhRCh/5pFWrVtSvXx+Anj17EhQUxHvvvccPP/zAAw884ODqrsxqtZKRkYGHh8dlH3/33XcZP348AwYM4L333sNisdgfe+GFF/j6669xcdGvw2t18eyYyPXSZRe5Id566y3Onz/PF198kSN4XFShQgX69+9/1X2EhYURExPD/v37b1SZV7Vv3z46duxIYGAgXl5eNGrU6JLAlJGRwcsvv0y9evXw9/fH29ubpk2b8uuvv16yv4SEBLp3746/vz8BAQF069aNhISEf63j4uWkCRMmXPLY/PnzsVgszJ49G4Bz584xYMAAypYti7u7OyVLluT222/n999/v6734NZbbwWwH4OsrCxee+01ypcvj7u7O2XLluX5558nPT3dvs3AgQMJCgri7xNm9+3bF4vFwgcffGBfFh8fj8Vi4ZNPPrEvS09PZ+jQoVSoUAF3d3ciIiIYPHhwjv2D7cuvT58+TJw4kWrVquHu7s68efMu+xpSU1MZMWIEVapU4Z133skRPC56+OGHadiwob19Lcf+4uW7qVOnMnz4cMqUKYOHhwe33XYbe/bsybHu7t27ad++PWFhYXh4eFCmTBk6d+5MYmIicPU+FBaLhVdeecXefuWVV7BYLOzatYuHHnoIf39/QkJCeOmllzDGcPjwYdq0aYOfnx9hYWG8++67l617ypQpPP/884SFheHt7c29997L4cOH7es1b96cOXPmcPDgQfvluLJly1613kWLFtG0aVO8vb0JCAigTZs2bN++Pcc6F+vfs2cP3bt3JyAgAH9/fx555BFSUlIuef1SNCnqyw3x448/Uq5cuf90GjszM5PDhw8TFBSUh5Vdm/j4eG666SZSUlLo168fQUFBTJgwgXvvvZfp06dz3333AZCUlMTnn3/OAw88QK9evTh37hxffPEFLVu2ZM2aNdSuXRuwnfZv06YNy5cv5/HHHycmJoYZM2bQrVu3f62lfv36lCtXjqlTp16y/pQpUyhRogQtW7YE4PHHH2f69On06dOHqlWrcvr0aZYvX8727dupW7durt+HvXv3AtiPQc+ePZkwYQIdOnTg6aefZvXq1YwYMYLt27fb++c0bdqUUaNGsXXrVqpXrw7AsmXLcHJyYtmyZfTr18++DODmm28GbGcv7r33XpYvX85jjz1GTEwMmzdvZtSoUezatYuZM2fmqG3RokVMnTqVPn36EBwcbP9i/Kfly5dz5swZBgwYgLOz87++5ms99heNHDkSJycnnnnmGRITE3nrrbfo0qULq1evBmwBtWXLlqSnp9O3b1/CwsL4888/mT17NgkJCfj7+/9rTZfTqVMnYmJiGDlyJHPmzOH1118nMDCQTz/9lFtvvZU333yTiRMn8swzz9CgQQP7+3zR8OHDsVgsPPvss5w4cYL333+fFi1asGHDBjw9PXnhhRdITEzkyJEjjBo1CgAfH58r1rNgwQJatWpFuXLleOWVV0hNTeXDDz+kcePG/P7775ccn/vvv5/o6GhGjBjB77//zueff07JkiV58803r+v9kELGiOSxxMREA5g2bdpc8zZRUVHmjjvuMCdPnjQnT540GzduNJ07dzaA6du3b4717r777svuY+3atQYw48aNu+pz/frrrwYw06ZNu+I6AwYMMIBZtmyZfdm5c+dMdHS0KVu2rMnOzjbGGJOVlWXS09NzbHv27FkTGhpqHn30UfuymTNnGsC89dZb9mVZWVmmadOm11TzkCFDjKurqzlz5ox9WXp6ugkICMjxPP7+/qZ3795X3dfljBs3zgBmwYIF5uTJk+bw4cNm8uTJJigoyHh6epojR46YDRs2GMD07Nkzx7bPPPOMAcyiRYuMMcacOHHCAObjjz82xhiTkJBgnJycTMeOHU1oaKh9u379+pnAwEBjtVqNMcZ8/fXXxsnJKcd7bowxY8aMMYBZsWKFfRlgnJyczNatW//1tY0ePdoAZsaMGdf0Xlzrsb/4OYqJicnxGbj4fJs3bzbGGPPHH3/86+dt//79V/wcAGbo0KH29tChQw1gHnvsMfuyrKwsU6ZMGWOxWMzIkSPty8+ePWs8PT1Nt27d7Msu1l26dGmTlJRkXz516lQDmNGjR9uX3X333SYqKuqa6q1du7YpWbKkOX36tH3Zxo0bjZOTk+natesl9f/9c2uMMffdd58JCgq67PsjRY8uu0ieS0pKAsDX1zdX2/3888+EhIQQEhJCrVq1mDZtGg8//LBD/hL66aefaNiwIU2aNLEv8/Hx4bHHHuPAgQNs27YNAGdnZ9zc3ADbX+5nzpwhKyuL+vXr57jU8dNPP+Hi4sITTzxhX+bs7Ezfvn2vqZ5OnTqRmZnJ999/b1/2888/k5CQQKdOnezLAgICWL16NUePHr2u192iRQtCQkKIiIigc+fO+Pj4MGPGDEqXLs1PP/0E2C6r/N3FTsIXL0uEhIRQpUoVli5dCsCKFStwdnZm0KBBxMfHs3v3bsB25qNJkyb2yyDTpk0jJiaGKlWqcOrUKfvPxUs//7yU1axZM6pWrfqvrym3n8drPfYXPfLII/bPANjO/IDt0g1gP7Mxf/78PL2s0LNnT/u/nZ2dqV+/PsYYevToYV8eEBBA5cqV7bX8XdeuXXO8Jx06dCA8PNx+nHPj2LFjbNiwge7duxMYGGhfXrNmTW6//fbL7vOf/biaNm3K6dOn7cdLijaFD8lzfn5+gK3/QW7Exsbyyy+/sGDBAn777TdOnTrFV199haenZ672c7lr+rl18OBBKleufMnymJgY++MXTZgwgZo1a+Lh4UFQUBAhISHMmTPHfj3/4vrh4eGXnLa+3HNcTq1atahSpQpTpkyxL5syZQrBwcH2L2ew9bXZsmULERERNGzYkFdeeeWyXzxX8tFHH/HLL7/w66+/sm3bNvbt22e/pHPw4EGcnJyoUKFCjm3CwsIICAjI8Z40bdrUflll2bJl1K9fn/r16xMYGMiyZctISkpi48aN9i9qsPWL2Lp1qz2AXvypVKkSACdOnMjxvNHR0df0mnL7eczNsQeIjIzM0S5RogQAZ8+etdc5cOBAPv/8c4KDg2nZsiUfffRRjs/H9fjn8/r7++Ph4UFwcPAlyy/W8ncVK1bM0bZYLFSoUIEDBw7kupaL78mV3rdTp06RnJx81fr/+b5J0aY+H5Ln/Pz8KFWqFFu2bMnVdsHBwbRo0eKq63h4eOQYH+TvLv5VmZ+98L/55hu6d+9O27ZtGTRoECVLlsTZ2ZkRI0bY+0vklU6dOjF8+HBOnTqFr68vs2bN4oEHHshxl8b9999vHx/l559/5u233+bNN9/k+++/p1WrVv/6HA0bNrTf7XIl1xLumjRpwmeffca+fftYtmwZTZs2xWKx0KRJE5YtW0apUqWwWq05wofVaqVGjRq89957l91nREREjva1htIqVaoAsHnzZtq2bXtN2+TGlfqRmL91uH333Xfp3r07P/zwAz///DP9+vVjxIgRrFq1ijJlylzxPc3Ozs7V815LLQVFYapV8p7OfMgN0bp1a/bu3cvKlSvzdL9RUVHs2rXrso/t3LnTvk5ePM/F/f3djh07cjzH9OnTKVeuHN9//z0PP/wwLVu2pEWLFqSlpV2yv2PHjnH+/PnL1nwtOnXqRFZWFt999x1z584lKSmJzp07X7JeeHg4Tz75JDNnzmT//v0EBQUxfPjwa36eK4mKisJqtdovm1wUHx9PQkJCjvf9Yqj45ZdfWLt2rb198803s2zZMpYtW4a3tzf16tWzb1O+fHnOnDnDbbfdRosWLS75udazRP/UpEkTSpQowbfffnvVL/O/v85rOfa5VaNGDV588UWWLl3KsmXL+PPPPxkzZgzw11/9/7z76Z9nWfLSP4+jMYY9e/bk6Bh6rWcRL74nV3rfgoOD8fb2vv5ipchR+JAbYvDgwXh7e9OzZ8/LjpC5d+9eRo8enev93nXXXRw5cuSSOx/S09PtveWv566Oyz3PmjVrcoSn5ORkxo4dS9myZe19DS7+9fb3v9ZWr159Sei66667yMrKynFbaXZ2Nh9++OE11xQTE0ONGjWYMmUKU6ZMITw8PMcdDNnZ2Zecyi9ZsiSlSpW65FbV63HXXXcBXDLi5cUzFXfffbd9WXR0NKVLl2bUqFFkZmbSuHFjwBZK9u7dy/Tp02nUqNElZ23+/PNPPvvss0ueOzU19ZLT9tfKy8uLZ599lu3bt/Pss89e9i/rb775hjVr1thf57Uc+2uVlJREVlZWjmU1atTAycnJflz8/PwIDg6295O56OOPP87Vc+XGV199leNS1PTp0zl27FiOM2Te3t7XdHkoPDyc2rVrM2HChBwBasuWLfz888/2z47IRbrsIjdE+fLlmTRpkv12wL+PcPrbb78xbdo0unfvnuv9PvbYY3z55Zd07NiRRx99lDp16nD69GmmTJnCli1b+Oqrr3J0/rua7777zv7X7N9169aN5557jm+//ZZWrVrRr18/AgMDmTBhAvv37+e7777DycmW21u3bs3333/Pfffdx913383+/fsZM2YMVatWzXGW45577qFx48Y899xzHDhwgKpVq/L999/n+rp/p06dePnll/Hw8KBHjx72OsDWp6FMmTJ06NCBWrVq4ePjw4IFC1i7du0lYz1cj1q1atGtWzfGjh1LQkICzZo1Y82aNUyYMIG2bdtyyy235Fi/adOmTJ48mRo1atj/sq9bty7e3t7s2rWLBx98MMf6Dz/8MFOnTuXxxx/n119/pXHjxmRnZ7Njxw6mTp3K/Pnz//WS0JVcHFH33Xff5ddff6VDhw6EhYVx/PhxZs6cyZo1a/jtt98ArvnYX6tFixbRp08fOnbsSKVKlcjKyuLrr7/G2dmZ9u3b29fr2bMnI0eOpGfPntSvX5+lS5de8SxfXggMDKRJkyY88sgjxMfH8/7771OhQgV69eplX6devXpMmTKFgQMH0qBBA3x8fLjnnnsuu7+3336bVq1aERcXR48ePey32vr7++cYp0QE0K22cmPt2rXL9OrVy5QtW9a4ubkZX19f07hxY/Phhx+atLQ0+3pXu4X2n86ePWueeuopEx0dbVxdXY2fn5+55ZZbzNy5c69p+4u3Gl7p5+Itlnv37jUdOnQwAQEBxsPDwzRs2NDMnj07x76sVqt54403TFRUlHF3dzd16tQxs2fPNt26dbvkFsXTp0+bhx9+2Pj5+Rl/f3/z8MMP22/D/LdbbS/avXu3vc7ly5fneCw9Pd0MGjTI1KpVy/j6+hpvb29Tq1Yt+y2vV3PxVtu1a9dedb3MzEwzbNgw+3sfERFhhgwZkuNYXvTRRx8ZwDzxxBM5lrdo0cIAZuHChZdsk5GRYd58801TrVo14+7ubkqUKGHq1atnhg0bZhITE+3rAdd1S/H06dPNHXfcYQIDA42Li4sJDw83nTp1MosXL86x3rUc+yvdsv3P21D37dtnHn30UVO+fHnj4eFhAgMDzS233GIWLFiQY7uUlBTTo0cP4+/vb3x9fc39999vv235crfanjx5Msf23bp1M97e3pe85mbNmplq1apdUve3335rhgwZYkqWLGk8PT3N3XffbQ4ePJhj2/Pnz5sHH3zQBAQEGMD+mb7SrcELFiwwjRs3Np6ensbPz8/cc889Ztu2bTnWuVL9Fz+D+/fvv+Q1SNFjMUa9e0REiovFixdzyy23MG3aNDp06ODocqSYUp8PERERyVcKHyIiIpKvFD5EREQkX6nPh4iIiOQrnfkQERGRfKXwISIiIvmqwA0yZrVaOXr0KL6+vnkyQZiIiIjceMYYzp07R6lSpf51ML4CFz6OHj16yQRSIiIiUjgcPnyYMmXKXHWdAhc+fH19AVvxF6fCFhERkYItKSmJiIgI+/f41RS48HHxUoufn5/Ch4iISCFzLV0m1OFURERE8pXCh4iIiOQrhQ8RERHJVwWuz8e1ys7OJjMz09FliFzCzc3tX28zExEpzgpd+DDGcPz4cRISEhxdishlOTk5ER0djZubm6NLEREpkApd+LgYPEqWLImXl5cGIpMC5eIgeceOHSMyMlKfTxGRyyhU4SM7O9sePIKCghxdjshlhYSEcPToUbKysnB1dXV0OSIiBU6hujB9sY+Hl5eXgysRubKLl1uys7MdXImISMFUqMLHRTqVLQWZPp8iIldXKMOHiIiIFF4KH4XcK6+8Qu3atR1dhoiIyDVT+BAREZF8pfDhIBkZGY4uoUDKzs7GarU6ugwRkaJr13w4tsmhJSh85JPmzZvTp08fBgwYQHBwMC1btuS9996jRo0aeHt7ExERwZNPPsn58+ft24wfP56AgABmzpxJxYoV8fDwoGXLlhw+fPi6aujevTtt27Zl2LBhhISE4Ofnx+OPP54jCKWnp9OvXz9KliyJh4cHTZo0Ye3atfbH69evzzvvvGNvt23bFldXV3vdR44cwWKxsGfPHvv+nnnmGUqXLo23tzexsbEsXrz4ktc4a9Ysqlatiru7O4cOHbqu1yciIleRmQZzn4VJ98P0RyEj2WGlFPrwYYwhJSPLIT/GmFzVOmHCBNzc3FixYgVjxozBycmJDz74gK1btzJhwgQWLVrE4MGDc2yTkpLC8OHD+eqrr1ixYgUJCQl07tz5ut+vhQsXsn37dhYvXsy3337L999/z7Bhw+yPDx48mO+++44JEybw+++/U6FCBVq2bMmZM2cAaNasmT08GGNYtmwZAQEBLF++HIAlS5ZQunRpKlSoAECfPn1YuXIlkydPZtOmTXTs2JE777yT3bt353iNb775Jp9//jlbt26lZMmS1/36RETkMk7uhM9bwOoxtnaFFmBxdlg5hWqQsctJzcym6svzHfLc215tiZfbtb+FFStW5K233rK3K1eubP932bJlef3113n88cf5+OOP7cszMzP53//+R2xsLGALMDExMaxZs4aGDRvmumY3Nze+/PJLvLy8qFatGq+++iqDBg3itddeIzU1lU8++YTx48fTqlUrAD777DN++eUXvvjiCwYNGkTz5s354osvyM7OZsuWLbi5udGpUycWL17MnXfeyeLFi2nWrBkAhw4dYty4cRw6dIhSpUoB8MwzzzBv3jzGjRvHG2+8YX+NH3/8MbVq1cr16xERkaswBn6fAHOfg6xU8AqCtp9ApZYOLavQh4/CpF69ejnaCxYsYMSIEezYsYOkpCSysrJIS0sjJSXFPpCai4sLDRo0sG9TpUoVAgIC2L59+3WFj1q1auUYpC0uLo7z589z+PBhEhMTyczMpHHjxvbHXV1dadiwIdu3bwegadOmnDt3jj/++IPffvuNZs2a0bx5c0aOHAnYznwMGjQIgM2bN5OdnU2lSpVy1JCenp5jhFo3Nzdq1qyZ69ciIiJXkXoWfuwP236wtcs1h/s+Bd8wh5YFRSB8eLo6s+1VxyQ4T9fcnbLy9va2//vAgQO0bt2aJ554guHDhxMYGMjy5cvp0aMHGRkZBXYU14CAAGrVqsXixYtZuXIlt99+OzfffDOdOnVi165d7N69237m4/z58zg7O7N+/XqcnXO+Vz4+PvZ/e3p6amAuEZG8dHAlfN8LEg+Dkwvc9jLE9YUCMuN2oQ8fFoslV5c+Cor169djtVp599137dOvT5069ZL1srKyWLdunf0sx86dO0lISCAmJua6nnfjxo2kpqbi6ekJwKpVq/Dx8SEiIoLg4GB7n5SoqCjAdklk7dq1DBgwwL6PZs2a8euvv7JmzRp7cIqJiWH48OGEh4fbz3TUqVOH7OxsTpw4QdOmTa+rXhERyYXsLFj2Dix5E4wVSkRDhy+gdL1/3zYfFYwIVAxVqFCBzMxMPvzwQ/bt28fXX3/NmDFjLlnP1dWVvn37snr1atavX0/37t1p1KjRdV1yAdstvj169GDbtm389NNPDB06lD59+uDk5IS3tzdPPPEEgwYNYt68eWzbto1evXqRkpJCjx497Pto3rw58+fPx8XFhSpVqtiXTZw40X7WA6BSpUp06dKFrl278v3337N//37WrFnDiBEjmDNnznXVLyIiV5BwGCa0hsUjbMGj1gPw+LICFzxA4cNhatWqxXvvvcebb75J9erVmThxIiNGjLhkPS8vL5599lkefPBBGjdujI+PD1OmTLnu573tttuoWLGi/VLJvffeyyuvvGJ/fOTIkbRv356HH36YunXrsmfPHubPn0+JEiXs6zRt2hSr1ZojaDRv3pzs7GyaN2+e4/nGjRtH165defrpp6lcuTJt27Zl7dq1REZGXvdrEBGRf9g6E8Y0hkMrwc0X2n0G940Bd19HV3ZZFpPb+0VvsKSkJPz9/UlMTMTPzy/HY2lpaezfv5/o6Gg8PDwcVGH+GT9+PAMGDCAhISFP9te9e3cSEhKYOXNmnuxPLq+4fU5FxIEyUmDec7Y7WsB2lqP95xBYLt9Ludr39z8Vvs4SIiIiAsc3w/QecGonYIEmA+CWF8DZ1dGV/SuFjyLk73eQ/NPcuXPzsRIREblhjIE1Y+HnFyE7A3zCoN2ntltpCwmFjwKse/fudO/e/ZrX37BhwxUfK126tO44EREp7JJPwQ+9Ydc8W7vSndDmY/AOuvp2BYzCRxFycUhzEREpgvYthu//D84fB2d3uON1aNgLCuE4SQofIiIiBVl2Jix6HVaMBgwEV4YOX0JYdUdXdt0UPkRERAqqM/tsnUqP/m5r1+sOLUeAW8EcBftaKXyIiIgURBunwJyBkHEePPzh3v9B1XsdXVWeUPgQEREpSNKS4KdnYNOFASUjb4J2YyEgwrF15SGFDxERkYLiz/W2yyxn94PFCZo9Bzc/A065m8i0oFP4KKQK42ilhbFmEZF8YbXCb6NtHUutWeAfYRupNLKRoyu7IRQ+CrgDBw4QHR3NH3/8Qe3ate3LR48eTX6MjK/AICJyg507DjP+z3YrLUDVtnDP++BZ4iobFW65nljuzz//5KGHHiIoKAhPT09q1KjBunXr7I8bY3j55ZcJDw/H09OTFi1asHv37jwtWsDf35+AgABHl1GsZWRkOLoEESnsds6DT26yBQ9XL7j3Q+g4vkgHD8hl+Dh79iyNGzfG1dWVuXPnsm3bNt59990cM56+9dZbfPDBB4wZM4bVq1fj7e1Ny5YtSUtLy/PiCxOr1cqIESOIjo7G09OTWrVqMX36dMD2vnbp0oWQkBA8PT2pWLEi48aNAyA6OhqAOnXqYLFY7LPGdu/enbZt29r337x5c/r27cuAAQMoUaIEoaGhfPbZZyQnJ/PII4/g6+tLhQoVcgyznp2dTY8ePew1Va5cmdGjR9sff+WVV5gwYQI//PADFosFi8XC4sWLATh8+DD3338/AQEBBAYG0qZNGw4cOJBj3wMHDiQgIICgoCAGDx6cqzM1zZs3p0+fPvTp0wd/f3+Cg4N56aWXcuzj7NmzdO3alRIlSuDl5UWrVq3sQdcYQ0hIiP09Bqhduzbh4eH29vLly3F3dyclJQWAhIQEevbsSUhICH5+ftx6661s3Lgxx/tRu3ZtPv/8c00aJyL/TWYa/DQYvu0EKachrAY8tgTqdi2Ug4blmsmFZ5991jRp0uSKj1utVhMWFmbefvtt+7KEhATj7u5uvv3222t6jsTERAOYxMTESx5LTU0127ZtM6mpqX9/UmPSzzvmx2q95vfu9ddfN1WqVDHz5s0ze/fuNePGjTPu7u5m8eLFpnfv3qZ27dpm7dq1Zv/+/eaXX34xs2bNMsYYs2bNGgOYBQsWmGPHjpnTp08bY4zp1q2badOmjX3/zZo1M76+vua1114zu3btMq+99ppxdnY2rVq1MmPHjjW7du0yTzzxhAkKCjLJycnGGGMyMjLMyy+/bNauXWv27dtnvvnmG+Pl5WWmTJlijDHm3Llz5v777zd33nmnOXbsmDl27JhJT083GRkZJiYmxjz66KNm06ZNZtu2bebBBx80lStXNunp6cYYY958801TokQJ891335lt27aZHj16GF9f3xw1X02zZs2Mj4+P6d+/v9mxY4e9trFjx9rXuffee01MTIxZunSp2bBhg2nZsqWpUKGCycjIMMYY065dO9O7d29jjDFnzpwxbm5uxt/f32zfvt1+TBo3bmzfX4sWLcw999xj1q5da3bt2mWefvppExQUZH/Phw4dary9vc2dd95pfv/9d7Nx48bL1n7Zz6mIyEUndhjz8U3GDPWz/cx9zpjMNEdX9Z9d7fv7n3LV52PWrFm0bNmSjh07smTJEkqXLs2TTz5Jr169ANi/fz/Hjx+nRYsW9m38/f2JjY1l5cqVdO7c+ZJ9pqenk56ebm8nJSXlLj1lpsAbpXK3TV55/ii4ef/raunp6bzxxhssWLCAuLg4AMqVK8fy5cv59NNPOX/+PHXq1KF+/foAlC1b1r5tSEgIAEFBQYSFhV31eWrVqsWLL74IwJAhQxg5ciTBwcH24/Pyyy/zySefsGnTJho1aoSrqyvDhg2zbx8dHc3KlSuZOnUq999/Pz4+Pnh6epKenp7jub/55husViuff/45lgsJfdy4cQQEBLB48WLuuOMO3n//fYYMGUK7du0AGDNmDPPnz//X9+rvIiIiGDVqFBaLhcqVK7N582ZGjRpFr1692L17N7NmzWLFihXcdNNNAEycOJGIiAhmzpxJx44dad68OZ9++ikAS5cupU6dOoSFhbF48WKqVKnC4sWLadasGWA7C7JmzRpOnDiBu7s7AO+88w4zZ85k+vTpPPbYY4DtUstXX31lPy4iItfMGPh9Asx9DrJSwSsY2n4Cle5wdGX5LleXXfbt28cnn3xCxYoVmT9/Pk888QT9+vVjwoQJABw/fhyA0NDQHNuFhobaH/unESNG4O/vb/+JiCg69zFftGfPHlJSUrj99tvx8fGx/3z11Vfs3buXJ554gsmTJ1O7dm0GDx7Mb7/9dl3PU7NmTfu/nZ2dCQoKokaNGvZlF4/LiRMn7Ms++ugj6tWrR0hICD4+PowdO5ZDhw5d9Xk2btzInj178PX1tb+WwMBA0tLS2Lt3L4mJiRw7dozY2Fj7Ni4uLvZwda0aNWpkDzcAcXFx7N69m+zsbLZv346Li0uO5wgKCqJy5cps374dgGbNmrFt2zZOnjzJkiVLaN68Oc2bN2fx4sVkZmby22+/2S9jbdy4kfPnzxMUFJTjGO3fv5+9e/fanyMqKkrBQ0RyL/UsTO0KP/a3BY9yt8ATK4pl8IBc3u1itVqpX78+b7zxBmDrh7BlyxbGjBlDt27drquAIUOGMHDgQHs7KSkpdwHE1ct2BsIRXK9teNvz588DMGfOHEqXLp3jMXd3dyIiIjh48CA//fQTv/zyC7fddhu9e/fmnXfeyV05rq452haLJceyi1/kVqsVgMmTJ/PMM8/w7rvvEhcXh6+vL2+//TarV6/+19dTr149Jk6ceMljBemLuUaNGgQGBrJkyRKWLFnC8OHDCQsL480332Tt2rVkZmbaz5qcP3+e8PBwe5+Wv/t7x15v738/0yUiksPBlfBdT0g6Ak4ucNtQiOsDTrm+56PIyFX4CA8Pp2rVqjmWxcTE8N133wHYT83Hx8fn6NgXHx+f4zbRv3N3d7ef5r4uFss1XfpwpKpVq+Lu7s6hQ4fsp/n/KSQkhG7dutGtWzeaNm3KoEGDeOedd3BzcwNsHTjz2sVLFk8++aR92d//ygdwc3O75Lnr1q3LlClTKFmyJH5+fpfdd3h4OKtXr+bmm28GICsri/Xr11O3bt1rru+fIWjVqlVUrFgRZ2dnYmJiyMrKYvXq1fYAcfr0aXbu3Gn/jFosFpo2bcoPP/zA1q1badKkCV5eXqSnp/Ppp59Sv359e5ioW7cux48fx8XFJcdlLxGR65adBUvfhqVvgbFCYDlo/wWUvvbfg0VVrmJX48aN2blzZ45lu3btIioqCrD1GQgLC2PhwoX2x5OSkli9erW9r0Nx5OvryzPPPMNTTz3FhAkT2Lt3L7///jsffvghEyZM4OWXX+aHH35gz549bN26ldmzZxMTEwNAyZIl8fT0ZN68ecTHx5OYmJhndVWsWJF169Yxf/58du3axUsvvcTatWtzrFO2bFk2bdrEzp07OXXqFJmZmXTp0oXg4GDatGnDsmXL2L9/P4sXL6Zfv34cOXIEgP79+zNy5EhmzpzJjh07ePLJJ0lISMhVfYcOHWLgwIHs3LmTb7/9lg8//JD+/fvba2/Tpg29evVi+fLlbNy4kYceeojSpUvTpk0b+z6aN2/Ot99+S+3atfHx8cHJyYmbb76ZiRMn5giCLVq0IC4ujrZt2/Lzzz9z4MABfvvtN1544YUct5KLiFyThMMwoTUsGWkLHrUegP9bquBxQa7Cx1NPPcWqVat444032LNnD5MmTWLs2LH07t0bsP2lOWDAAF5//XVmzZrF5s2b6dq1K6VKlcpxW2hx9Nprr/HSSy8xYsQIYmJiuPPOO5kzZw7R0dG4ubkxZMgQatasyc0334yzszOTJ08GbH0lPvjgAz799FNKlSqV44v1v/q///s/2rVrR6dOnYiNjeX06dM5zoIA9OrVi8qVK1O/fn1CQkJYsWIFXl5eLF26lMjISNq1a0dMTAw9evQgLS3Nfibk6aef5uGHH6Zbt272Szr33Xdfrurr2rUrqampNGzYkN69e9O/f397x0+wdXKtV68erVu3Ji4uDmMMP/30U45LTc2aNSM7O9vetwNsgeSfyywWCz/99BM333wzjzzyCJUqVaJz584cPHjwkj5MIiJXtXUmjGkMh1aCmy+0+xzuGwPuvo6urMCwGJO7YTJnz57NkCFD2L17N9HR0QwcONB+NwXYxlcYOnQoY8eOJSEhgSZNmvDxxx9TqVKla9p/UlIS/v7+JCYmXnJKPy0tjf3792uMhWKgefPm1K5dm/fff9/RpeSaPqcixVRGMswbYrujBaB0PdtllsBox9aVT672/f1PuR5evXXr1rRu3fqKj1ssFl599VVeffXV3O5aRESkcDq+GaY/Cqd2ARZo8hTc8jw4u/7rpsWR5naRfHfo0KFLOi7/3bZt2/KxGhGR/8AYWP0p/PISZGeATxi0GwvlLn9zgdgofEi+K1WqFBs2bLjq45e75VVEpEBJPgUzn4TdFwZQrNQK2nwE3kGOrasQUPiQfOfi4kKFChUcXYaIyPXb+6ttJtrz8eDsDne8Dg17FY95WfJAoQwfuewjK5Kv9PkUKcKyMuDX12HFB4CBkCq2TqVh1R1dWaFSqMLHxVsoU1JS8PT0dHA1IpeXkZEB2Ia4F5Ei5OwBmPYIHP3d1q73CLR8A9yubbRr+UuhCh/Ozs4EBATY5ybx8vLKMfeHiKNZrVZOnjyJl5cXLi6F6n8vEbmaXfPh+16QlggeAXDvh1D1XkdXVWgVut+OF4dw//vkaCIFiZOTE5GRkQrGIkWBNRsWj7QNkQ5Quj50HA8BRW8S1PxU6MKHxWIhPDyckiVLkpmZ6ehyRC7h5uaGUzGeMEqkyEg+Dd/3hL2LbO0GvWyXWVzcHFtXEVDowsdFzs7OuqYuIiI3xpH1MLWrbSZaF0+49wOoeb+jqyoyCm34EBERyXPGwLovYd5ztkHDAstDp68htJqjKytSFD5EREQAMlJgzkDY+K2tXaU1tP0YPPwdW1cRpPAhIiJyeq/tMkv8FrA4QYtX4KZ+GjTsBlH4EBGR4m3HHJjxOKQngXcIdBgH0U0dXVWRpvAhIiLFU3aWbbTS5aNs7YhGttto/cIdWlZxoPAhIiLFz/mT8N2jsH+prd3oSbj9VXB2dWxdxYTCh4iIFC+H18DUbnDuKLh6Q5sPoXp7R1dVrCh8iIhI8WAMrBkL858HaxYEV4L7v4aSVRxdWbGj8CEiIkVfRjLM6gdbptvaVdtCm/+Bu69DyyquFD5ERKRoO7UbpjwMJ7eDkwvc/ho0ekK30TqQwoeIiBRd236Amb0h4xz4hNnuZomKc3RVxZ7Ch4iIFD3ZWbBgKKz8n60d1QQ6fAm+oY6tSwCFDxERKWrOxcP0R+DgClv7pr5w2yvgrK+8gkJHQkREio6Dv8G07nA+Htx8oe1HULWNo6uSf1D4EBGRws8YWPUx/PwSmGwIqQKdvoHgio6uTC5D4UNERAq39HPwQx/YNtPWrt4B7hkN7j4OLUuuTOFDREQKrxM7YOrDcGqX7TbaliOgYS/dRlvAKXyIiEjhtOU7+KEvZCaDbym4fwJENHR0VXINFD5ERKRwycqAX16G1Z/Y2mWbQodx4BPi2Lrkmil8iIhI4ZF01HY3y+HVtnaTp+CWF3UbbSGjoyUiIoXD/qUw/VFIPgnufnDfGKhyt6Orkuug8CEiIgWbMbBiNCwcBsYKodXh/q8gqLyjK5PrpPAhIiIFV1oizHwSdsy2tWt2htajwM3LsXXJf6LwISIiBVP8VttstGf2grMb3DkS6j+q22iLAIUPEREpeDZNhVn9ICsV/MrYLrOUqefoqiSPKHyIiEjBkZUB85+HtZ/Z2uVugfZfgHeQY+uSPKXwISIiBUPiEZjaDf5cZ2vfPBiaPwdOzo6tS/KcwoeIiDjevsW222hTToOHP7T7DCq1dHRVcoMofIiIiONYrbD8Pfh1uO022rCa0OlrKFHW0ZXJDaTwISIijpGaADMeh11zbe06D8Fd74Crp0PLkhtP4UNERPLfsU222WjPHgBnd7j7Hajb1dFVST5R+BARkfy1YRLMfgqy0iAg0nYbbak6jq5K8pFTblZ+5ZVXsFgsOX6qVKlifzwtLY3evXsTFBSEj48P7du3Jz4+Ps+LFhGRQigrwxY6Zj5hCx4V74DHlih4FEO5Ch8A1apV49ixY/af5cuX2x976qmn+PHHH5k2bRpLlizh6NGjtGvXLk8LFhGRQuhcPEy4B9Z9CVig+fPwwBTwCnR0ZeIAub7s4uLiQlhY2CXLExMT+eKLL5g0aRK33norAOPGjSMmJoZVq1bRqFGj/16tiIgUPkfWw5SH4NxRcPeH9p9DpTscXZU4UK7PfOzevZtSpUpRrlw5unTpwqFDhwBYv349mZmZtGjRwr5ulSpViIyMZOXKlVfcX3p6OklJSTl+RESkiPhjIoxrZQsewZWh1yIFD8ld+IiNjWX8+PHMmzePTz75hP3799O0aVPOnTvH8ePHcXNzIyAgIMc2oaGhHD9+/Ir7HDFiBP7+/vafiIiI63ohIiJSgGRnwtxn4YcnITsdKt8FPRdAcAVHVyYFQK4uu7Rq1cr+75o1axIbG0tUVBRTp07F0/P67sseMmQIAwcOtLeTkpIUQERECrPkU7Zh0g9e6BPYfIhtqHSnXJ9slyLqP91qGxAQQKVKldizZw+33347GRkZJCQk5Dj7ER8ff9k+Ihe5u7vj7u7+X8oQEZGC4ugGW/+OxMPg5gPtxkKVux1dlRQw/ymGnj9/nr179xIeHk69evVwdXVl4cKF9sd37tzJoUOHiIuL+8+FiohIAbdpKnzZ0hY8AstDz4UKHnJZuTrz8cwzz3DPPfcQFRXF0aNHGTp0KM7OzjzwwAP4+/vTo0cPBg4cSGBgIH5+fvTt25e4uDjd6SIiUpRlZ8GCobDyf7Z2xTtsE8N5Bji0LCm4chU+jhw5wgMPPMDp06cJCQmhSZMmrFq1ipCQEABGjRqFk5MT7du3Jz09nZYtW/Lxxx/fkMJFRKQASDkD0x+xzUoL0PQZuOV5cHJ2aFlSsFmMMcbRRfxdUlIS/v7+JCYm4ufn5+hyRETkSo5vgckPQsJBcPWGth9DtbaOrkocJDff35rbRUREcm/rDJj5JGSmQImy0HkShFZzdFVSSCh8iIjItbNmw6LXYPkoW7vcLdDhSw2TLrmi8CEiItcm9Sx81xP2LLC1b+oHtw0FZ32VSO7oEyMiIv/uxHZb/44z+8DFE9r8D2p0cHRVUkgpfIiIyNVt/xFmPA4Z58E/Ejp/A+G1HF2VFGIKHyIicnlWKywZCUvetLXLNoWOE8A7yLF1SaGn8CEiIpdKS4LvH4Ndc23t2CfgjtfA2dWxdUmRoPAhIiI5ndpt699xahc4u8M9o6H2A46uSooQhQ8REfnLznnwfS9ITwK/0tDpGyhd19FVSRGj8CEiIrb+HcvehV+HAwYi4+D+r8CnpKMrkyJI4UNEpLhLPwczn7Dd1QLQoCe0HAEubo6tS4oshQ8RkeLs9F6Y3AVObgdnN7jrHajXzdFVSRGn8CEiUlztWQDTH4W0RPAJg05fQ0RDR1clxYDCh4hIcWMMrBgNC4eBsUKZBnD/1+AX7ujKpJhQ+BARKU4ykuGHPrD1e1u7blfbpRYXd8fWJcWKwoeISHFx9gBMfgjiN4OTC7R6C+o/ChaLoyuTYkbhQ0SkONi3GKZ1t81M6x1iu4026iZHVyXFlMKHiEhRZgys+gR+fhFMNpSqYxs4zL+MoyuTYkzhQ0SkqMpMhR/7w6YptnatB6H1KHD1cGxdUuwpfIiIFEUJh2FKFzi2ESzO0PINiP0/9e8oxrKthmOJqRw6nUKW1XBzpRCH1aLwISJS1BxYAVO7Qsop8AqCjuMh+mZHVyX5ICPLypGzKRw8ncLB08kcOJ3CoTMpHDidzJEzqWRkWwGoEuar8CEiInnAGFj7Ocx7DqxZEFYTOk+EgEhHVyZ5KCUj60K4sAWMg2cu/Pd0CkcTUrGaK2/r6mwhItCL8iE++VfwZSh8iIgUBZlp8NPT8Mc3tnb1DnDvh+Dm5di65LokpmRy4GKwOPVXwDhwOoWT59Kvuq2XmzORgV6UDfImKsiLKPt/vQj398TZyfGX3hQ+REQKu6SjMOVh+HMdWJzg9lchro/6dxRgxhhOnkvn4JkUDpxKvnBpJIVDFwJGYmrmVbcP8HK1hYpAL8oGeREZ5H3hv16E+LhjKeDHXuFDRKQwO7Qapj4M5+PBIwA6joPytzq6KsHWwfNoQqq9z4X9MsmFfhgpGdlX3b6krztlg7yJDMoZMKICvfH3cs2nV3FjKHyIiBRW68bBT4PAmgklq9n6dwRGO7qqYiU9K5sjZ1PtoeLvAePw2RQys6/cAcPJAqVLeBIV+NdlkYuXSCIDvfByK7pf0UX3lYmIFFVZGTB3MKwfZ2tXbQNtPgZ3x3YiLMoys61s/jOR9QfOsu9U8l8dPBNTMVfp4Onm7EREoOdf/S4CvYgK9qZskDelAzxxc3HKvxdRgCh8iIgUJufibbfRHl4FWOC2l6DJQPXvyGPZVsOWPxNZue80q/adZu3+MyRf4TKJt5tzjj4XZS/0xYgK9ibMz6NAdPAsaBQ+REQKiyPrYcpDcO4ouPtDhy+g4u2OrqpIsFoN244lsWrfaVbuPc2a/Wc4l56VYx1/T1caRgcSE+ZLVJA3ZYO9iAz0JtjHrcB38CxoFD5ERAqDP76B2U9BdgYEV4YHvoWg8o6uqtCyWg0748+xcq/tzMbq/WcuucPE18OF2OhAGpULIq58EDFhfjjpLEaeUPgQESnIsjNh/guw5lNbu0praPsJePg5tq5CxhjDnhPnWXnhzMbq/Wc4k5yRYx1vN2ca/i1sVCvlr0smN4jCh4hIQZV8CqZ2g4PLbe3mz8PNg8CpeHZSzA1jDPtOJdvPbKzad4ZT53MOzuXp6kz9siWIKx9EXLkgapT2x8VZ721+UPgQESmIjqyDad0h8TC4+UK7sVDlLkdXVWAZYzh0JoWVe0/bO4nGJ+UMG+4uTrawceHMRo3SAcX2bhNHU/gQESlI0s/Botdh9aeAgaAK0HkShFR2dGUFzuEzKbagceHsxtHEtByPuzk7UScywH5mo3ZkAO4uzg6qVv5O4UNEpKDY8RP89Awk/Wlr1+wMrd4EzwCHllVQHE1Itd+NsnLfaY6cTc3xuKuzhdoRAcSVC6JR+SDqRpbAw1VhoyBS+BARcbSkYzB3EGz/0dYuEQ2tR0H5Wxxbl4OdSEqzdxBdue80B0+n5HjcxclCzTL+9g6i9aJKFOlRQYsSHSUREUexWmH9l7BgGKQngZML3NQPmg0GV09HV5fvTp1Pz3FmY9/J5ByPO1mgRml/Gl24jNKgbCDe7voaK4x01EREHCF+G/zYH46ssbVL14d7P4DQao6tKx+dSc5g9b7T9rMbu0+cz/G4xQLVSvnZLqOUC6JBdCB+HoV7QjWxUfgQEclPmamw9G1YMRqsWbY7WVoMhfqPglPR7p9w6nw66w6cYfX+M6zce5odx89dsk6VMF97B9HY6KBCP3urXJ7Ch4hIftm32DZK6Zl9tnaV1nDX2+BXyqFl3QgXb31ds/8M6w6cZe2BM+w7lXzJepVCfey3vjaMDiLQ280B1Up+U/gQEbnRkk/Dzy/Cxkm2tm8pW+iIae3YuvJQttWw/VgS6w6cYe2FsHHiXPol61UO9aVBdAkaXbiUEuzj7oBqxdH+U/gYOXIkQ4YMoX///rz//vsApKWl8fTTTzN58mTS09Np2bIlH3/8MaGhoXlRr4hI4WEMbJoC84ZA6hnAAg17wa0vFfrh0dMys9l4OIG1F8LG7wfPXjIRm6uzhZplAmhQNpAGZUtQPypQl1EE+A/hY+3atXz66afUrFkzx/KnnnqKOXPmMG3aNPz9/enTpw/t2rVjxYoV/7lYEZFC4/Re2yWW/Uts7ZLVbB1Ky9R3bF3XKTElk3UH/zqrsflIIhnZ1hzr+Li7UDeqBA3LlqBB2UBqRQRonA25rOsKH+fPn6dLly589tlnvP766/bliYmJfPHFF0yaNIlbb70VgHHjxhETE8OqVato1KhR3lQtIlJQZWfCbx/AkrcgKw1cPKDZs3BTX3AuPH/1H01IvXBWw9ZnY2f8OYzJuU6IrzsNL57VKBtITLifJmKTa3Jd4aN3797cfffdtGjRIkf4WL9+PZmZmbRo0cK+rEqVKkRGRrJy5UqFDxEp2g6vtd0+e2KrrV3uFmj9HgSWc2xd/+LijK9rLgSNNfvP8GdC6iXrlQv2pkHZQOqXLUHD6EAiA72wWBQ2JPdyHT4mT57M77//ztq1ay957Pjx47i5uREQEJBjeWhoKMePH7/s/tLT00lP/6tTUlJSUm5LEhFxrLQkWPgqrP0cMOAVBC1HQM37bYNVFDAZWVa2HE1k3YEzrNl/lvUHz3A2JTPHOs5OFqqV8qN+VCANo0tQLyqQEF91DpW8kavwcfjwYfr3788vv/yCh4dHnhQwYsQIhg0blif7EhHJd9t/hJ8Gw7mjtnbtLnD7a+Ad5Ni6/iY5PYvfD51l7X5bn40/Dp8lLTNnfw0PVyfqRJSgQbTtMkqdyBL4aPRQuUFy9clav349J06coG7duvZl2dnZLF26lP/973/Mnz+fjIwMEhIScpz9iI+PJyws7LL7HDJkCAMHDrS3k5KSiIiIyOXLEBHJZ4l/wtzBsGO2rR1YDlq/D+WaObQsgJPn0nPc8rrtWBLZ1pwdNkp4uVL/Qn+NBmUDqVbKX9PLS77JVfi47bbb2Lx5c45ljzzyCFWqVOHZZ58lIiICV1dXFi5cSPv27QHYuXMnhw4dIi4u7rL7dHd3x91dp/JEpJCwZtsuryx8DTLO2eZjaTwAbn7GIfOxGGM4eDolR+fQyw3mVaaE54VbXm2Bo3yID07qHCoOkqvw4evrS/Xq1XMs8/b2JigoyL68R48eDBw4kMDAQPz8/Ojbty9xcXHqbCoihd/xLfBjP/hzva1dpiHcMxpCq+ZbCRcH87oYNNYcOMPJfwzmZbFcGMzrb51Dw/2L30R1UnDl+QW9UaNG4eTkRPv27XMMMiYiUmhlpMCSN2Hl/2zzsbj7QYtXoN4j4HRjL1WkZWaz4XCCrXPohcG8zv9jMC83ZydqlvGnftkLnUMjNZiXFGwWY/5557ZjJSUl4e/vT2JiIn5+hXsEQBEpAvYusg0WdvaArR1zL7R6C/zCb9hTJqRkMH39EeZuOc6mIwlkZuf8Ne17cTCv6EDqR5XQYF5SIOTm+1tdmUVELif5FMx/3jY8OoBfabjrHahy1w15OmMMvx9KYOLqg8zedIyMrL/uRinp6267CyXKdjdKlTAN5iWFm8KHiMjfGQMbJsHPL0DqWcACsY/DrS+Au2+eP925tExmbjjKxFUHc0wxX62UH50bRnJzxWAN5iVFjsKHiMhFp/bA7AFwYJmtHVoD7h0Npevl+VNt+TORiasP8cOGP0nJyAZsY23cU7MUXRpFUauMvwKHFFkKHyIiWRnw22hY8jZkp4OLJ9wyBBo9mafzsaRmZPPjpqNMXH2IjYcT7MsrlPShS2wk7eqUUUdRKRYUPkSkeDu02jYfy8nttnb522zzsZQom2dPsTv+HBNXH+K7349wLs12p4qrs4VW1cPpEhtJw+hAneWQYkXhQ0SKp9QEWDgM1n1pa3sFQ6s3oXr7PJmPJT0rm3lbjjNx9SHW7D9jXx4Z6MWDsZF0qFeGYB8NsCjFk8KHiBQvxsD2Wbb5WM5fmPCyzkO2+Vi8Av/z7g+eTmbSmkNMW3eEM8kZgG2SthYxJekSG0WTCsEaWVSKPYUPESk+Eo/AnGdg11xbO6iCbT6W6Kb/abdZ2VYWbD/BxNUHWbb7lH15mJ8HDzSMpFODCML882YyTpGiQOFDRIo+azasGWubjyUzGZxcoclT0PRpcL3+UHA0IZXJaw8zZe0h4pNsQ5xbLNCsUghdYqO4pXIILs6arE3knxQ+RKRoO7bR1qH06B+2dkQj23wsJatc1+6yrYalu08ycdUhFu2I5+JkscE+btxfP4IHGkYSEeiVR8WLFE0KHyJSNGUkw+KRsPIjMNng7g+3D4O63a5rPpaT59KZuu4w3645xJGzqfblceWC6NIokjuqhmlKepFrpPAhIkXP7gUw5ylIOGRrV7sP7hwJvmG52o0xhpX7TjNx9SF+3nrcPseKn4cLHepF8GBsJBVK+uR19SJFnsKHiBQd50/AvCGwZbqt7R8Bd78LlVrmajcXJ3abtOYQ+04m25fXiQygS2wUrWuGayI3kf9A4UNECj9j4I+v4eeXIC0BLE4Q+wTc8jy4X9uZib9P7DZn0zHSL0zs5u3mTNs6pXkwNpJqpfxv4IsQKT4UPkSkcDu1G34cAAeX29phNeHeD6BUnWva/EoTu8WE+/FQo0ja1C6Nj7t+VYrkJf0fJSKFU1Y6LH8flr0D2Rng6mU70xH7BDj/+6+2LX8mMmnNIX7440+SL0zs5u7ixD21StElNpLaEQEa8lzkBlH4EJHC5+BvtttnT+2ytSvcbuvbUSLqqpulZmQz+8LEbhv+NrFb+RBvusRG0b6uJnYTyQ8KHyJSeKSehQWvwPrxtrZ3iG0+lmrtrjofy54TFyZ2W3+EpL9N7HbnhYndYjWxm0i+UvgQkYLPGNj6Pcx9DpJP2JbV7WYbt8OzxGU3Sc/KZv7WeCauOsjqv03sFhHoyYMNo+hYXxO7iTiKwoeIFGwJh2DO07D7Z1s7uJJthNKomy67+qHTKRcmdjvM6QsTuzlZoEVMKF0aRdFUE7uJOJzCh4gUTNlZsHoM/DocMlPA2c02F0uTp8Al5xmLrGwrC3ecYOLqQyzdddK+PMzPg84NI+jUIIJwf8/8fgUicgUKHyJS8BzdAD/2s83LAhB5k+1sR0ilHKsdS0xl8prDTP7HxG43VwyhS2wkt1YpqYndRAoghQ8RKTjSz8PiEbDqYzBW8PCH21+DOg/b52OxXpzYbfUhFm7/a2K3IG837m8QwQMNIokM0sRuIgWZwoeIFAy7foY5AyHxsK1dvT20HAG+oYBtYrdp620Tux0+89fEbo3KBdIlNoo7qoXi7qIhz0UKA4UPEXGs9PO2DqWbJtva/pHQ+j2oeDvGGFbtPc3E1QeZf9mJ3SKoUNLXgcWLyPVQ+BARxzm5E6Z2hZM7bPOxNHoSbnmehCxXvlu+n4mrD+aY2K12RABdYiNpXbMUnm46yyFSWCl8iIhjbPkOfugLmcngE4bpOI4/LDFMnLmH2ZuO2id287o4sVvDSKqX1sRuIkWBwoeI5K+sDPj5RVjzKQCmbFPmVxnO6JlJbD/2m321KmG+PNQoija1S+HroSHPRYoShQ8RyT+JR2BadziyFoDTdfrQ51grVs48AtgmdmtdsxRdGkVSRxO7iRRZCh8ikj/2LoLvekLKaYyHP9MjX2TI6jJkWRPxcHWid/MKPBwXRYCXm6MrFZEbTOFDRG4sqxWWvm0bvwNDYkBVHk3pw/pNAYDh9qqhvNy6KhGBGptDpLhQ+BCRGyf5NHzfC/YuBGCxz1383/H7SceNMiU8GXZvNW6LCXVwkSKS3xQ+ROTGOLLedhtt0hEyndx5MfNRppxqiquzhb7NyvNk8wq6XVakmFL4EJG8ZQys/RzmDQFrJkcs4fRM7c8OE0mTCsEMa1ON8iE+jq5SRBxI4UNE8k76eZg9ADZPA2BudgMGZ/4fnr4l+LB1VVrXDNcdLCKi8CEieeTkTsyUrlhO7SDLODEi6wHGm7vp3iSaAS0qaqwOEbFT+BCR/27Ld2TP7INzVgrxJoDeGf0wkXH82KY6VUv5Obo6ESlgFD5E5PplZZA6Zwief3yOM/BbdlVecnmK/2sXR4d6ZXBy0iUWEbmUwoeIXJfss4c5M/4BQhI3A/BR1r0crTOQ6XdWo4S3BgoTkStT+BCRXNu3ahbB83sTYpJINF687/s099zfg7qRJRxdmogUAgofInLNEpPTWff1EG459iVOFsM2E822Jh/ywq2NcXF2cnR5IlJIKHyIyL8yxjB75RaCfunDbWYDWOA3/9ZU6P4RHUoEOLo8ESlkcvWnyieffELNmjXx8/PDz8+PuLg45s6da388LS2N3r17ExQUhI+PD+3btyc+Pj7PixaR/LMr/hzP/28Cdee34SazgTTc2H3TW9z01ERKKniIyHWwGGPMta78448/4uzsTMWKFTHGMGHCBN5++23++OMPqlWrxhNPPMGcOXMYP348/v7+9OnTBycnJ1asWHHNBSUlJeHv709iYiJ+frpFT8RRktOz+GDBLtJXjuV5569ws2ST4BmJ90MTcS1d09HliUgBk5vv71yFj8sJDAzk7bffpkOHDoSEhDBp0iQ6dOgAwI4dO4iJiWHlypU0atQoz4sXkbxnjGHeluO8/eN6+qd+RBvn3wBIKX8XXh3HgIe/gysUkYIoN9/f193nIzs7m2nTppGcnExcXBzr168nMzOTFi1a2NepUqUKkZGRVw0f6enppKen5yheRBzjwKlkhs7aypHdGxjj+j6VnP/EanHG6fZX8YrrDRoaXUTyQK7Dx+bNm4mLiyMtLQ0fHx9mzJhB1apV2bBhA25ubgQEBORYPzQ0lOPHj19xfyNGjGDYsGG5LlxE8k5aZjZjluzl48V7ucO6glluY/G2pGN8wnDqOB6i4hxdoogUIbkOH5UrV2bDhg0kJiYyffp0unXrxpIlS667gCFDhjBw4EB7OykpiYiIiOven4jkzuKdJxg6aytHTyfxvMtEHnGbb3ugbFMsHb4En5KOLVBEipxchw83NzcqVKgAQL169Vi7di2jR4+mU6dOZGRkkJCQkOPsR3x8PGFhYVfcn7u7O+7u7rmvXET+k6MJqbw2extztxwnnNPM8PyA6ma37cEmA+GWF8BZd+OLSN77z79ZrFYr6enp1KtXD1dXVxYuXEj79u0B2LlzJ4cOHSIuTqdsRQqKzGwr41bs5/0Fu0nJyKaZ82Y+8fwYr6xEW2fS+8ZC5TsdXaaIFGG5Ch9DhgyhVatWREZGcu7cOSZNmsTixYuZP38+/v7+9OjRg4EDBxIYGIifnx99+/YlLi7umu90EZEba/W+07z0wxZ2xZ/HgpWRQfPolDwRS5aB8Fpw/1dQoqyjyxSRIi5X4ePEiRN07dqVY8eO4e/vT82aNZk/fz633347AKNGjcLJyYn27duTnp5Oy5Yt+fjjj29I4SJy7U6dT+eNn7bz/e9/AlDOK41JQV8QdvLCGDz1usOdb4Krh+OKFJFi4z+P85HXNM6HSN7JthomrTnE2/N2kJSWhcUCg6qf5/Hjw3A69ye4eELr96D2g44uVUQKuXwZ50NECraNhxN46YctbDqSCEC1cF/GVP6DiDWvgTUTAsvbLrOEVXdwpSJS3Ch8iBQxiSmZvP3zDiauPoQx4OvuwpAWEXSOfxenVdNtK8XcA20+0milIuIQCh8iRYQxhu9//5M3ftrO6eQMAO6rU5oXY50Imt0dTu0EizPc/ipotFIRcSCFD5EiYOfxc7w0cwtrDpwBoEJJH15rU5241MUwsS9kJoNvOHQYp9FKRcThFD5ECrHk9CxGL9zNF8v3k201eLo6079FRR5tVBq3hS/Dmk9tK5ZtChqtVEQKCIUPkULo4syzr87exrHENABaVgvl5XuqUdpyGr66G/5cZ1tZo5WKSAGj30YihcyBU8m8PGsrS3edBCAi0JNh91bj1iqhsGchfNcTUs9otFIRKbAUPkQKibTMbD5ZvJdPluwlI8uKm7MTjzcvz5PNy+PhbIHFI20/aLRSESnYFD5ECoFfd57glVlbOXg6BYCmFYN5tU11ooO9Ifk0fN8L9i60razRSkWkgFP4ECnATp9P5+VZW5mz6RgAYX4evNS6KnfVCMNiscCR9TC1KyQduTBa6Sio/YCDqxYRuTqFD5ECau7mY7w4cwunkzNwdrLwaOOy9G9RCR93FzAG1nwG84b8NVppp68htJqjyxYR+VcKHyIFzNnkDIbO2sqsjUcBqBzqy7v316J66Qujkaafhx/7wxaNVioihZPCh0gB8vPW4zw/Ywunzqfj7GThiWbl6XtbBdxdnG0rnNwJUx7WaKUiUqgpfIgUAAkpGQz7cRsz/rBNeV+xpA/vdKxFrYiAv1baPB1m9dNopSJS6Cl8iDjYwu3xDPl+MyfOpeNkgcduLs+AFhXxcL1wtiMrA35+8a/RSqNvhvZfaLRSESm0FD5EHCQxNZPXZm9j+vojAJQL8eadjrWoG1nir5XOHoTpj/41WmnTp22jlTo5O6BiEZG8ofAh4gCLd57gue82czwpDYsFejaJ5uk7Kv91tgNg+2z44UlIS9RopSJSpCh8iOSjpLRMhs/ezpR1hwGIDvbm7Q41qV828K+VstLhl5dh9Rhbu0wD26RwAZEOqFhEJO8pfIjkk2W7T/Ls9E0cTbSd7XjkpmgGtayMp9vfznac2Q/TusOxDbb2TX3htqHg7OqIkkVEbgiFD5Eb7Hx6Fm/8tJ1Jqw8BEBnoxdsdahJbLijniltnwqy+kJ4EniXgvk+hUsv8L1hE5AZT+BC5gX7bc4pB0zfxZ0IqAN3ioni2VRW83P72v15mGvz8Aqz93NaOaAQdvgD/Mg6oWETkxlP4ELkBktOzeHPeDr5aeRCAMiU8eatDTW4qH5xzxdN7bZdZjm+ytZs8ZbubRZdZRKQIU/gQyWOr951m0PRNHDpjm4G2S2wkQ+6Ksc3J8nebp8OPAyDjHHgF2e5mqdgi/wsWEclnCh8ieSQ1I5u35u9g3IoDAJTy9+DNDjVpWjEk54qZqbYJ4daPs7WjGkP7z8GvVP4WLCLiIAofInlg7YEzDJq2kQOnbWc7OjeI4IW7Y/D1+Mflk1O7bZdZ4rcAFrj5GWj2HDjrf0URKT70G0/kP0jLzOad+Tv5YsV+jIEwP9vZjmaVQi5dedNU22WWzGTwDoF2Y6H8rfles4iIoyl8iFyn3w+d5ZmpG9l3KhmAjvXK8GLrqvh7/uNsR0YKzB0Mf3xta5dtarvM4huWzxWLiBQMCh8iuZSWmc2oBbv4bOk+rAZK+rozsn0Nbq0SeunKJ3faLrOc2AZYoNmz0Gyw5mYRkWJN4UMkFzYcTuCZaRvZc+I8AO3qlmZo62r4e13m1tgNk2DO05CZAj6h0O4zKNcsnysWESl4FD5ErkF6VjajF+xmzJK9WA0E+7gzol0Nbq96mbMdGckw5xnYOMnWLtfcFjx8SuZrzSIiBZXCh8i/2HwkkWembWRn/DkA2tQuxSv3VKOEt9ulK8dvs11mObUTLE7Q/HloOlCXWURE/kbhQ+QKMrKs/G/Rbj5avJdsqyHI243h91Xnzurhl65sjK1D6U+DISsVfMNtnUrLNsn/wkVECjiFD5HL2Ho0kaenbmTHcdvZjrtrhvPqvdUI8nG/dOX08zD7Kdg81dYuf5vtNlrv4EvXFRERhQ+Rv8vMtvLxr3v5cNFusqyGEl6uvNa2Oq1rXmH00eNbYFo3OL0HLM5w64vQeAA4OeVr3SIihYnCh8gFO44n8fTUjWw9mgRAy2qhvN62BiG+lznbYQysHw9zn4XsdPArDe2/gKi4/C1aRKQQUviQYi8r28qYJXsZvXA3mdmGAC9Xht1bjXtrlcJisVy6QVoSzB4AW76ztSu2hLafgHdQvtYtIlJYKXxIsbYr/hzPTNvIpiOJALSICeWNdtUp6etx+Q2ObbTdzXJmHzi5wG1DIa6PLrOIiOSCwocUS1nZVj5btp9Rv+wiI9uKn4cLw9pUo23t0pc/22EMrP0c5j8P2RngHwEdvoSIhvlfvIhIIafwIcXOnhPneWbaRjYcTgDglsohjGxfk1C/K5ztSEuEWX1h2w+2duW7oM1H4BWYPwWLiBQxCh9SbGRbDV8u38/bP+8kI8uKr7sLL99TlQ71ylz+bAfAn7/D9Efg7AFwcoXbh0GjJ+FK64uIyL9S+JBiYd/J8wyavon1B88CcHOlEN5sX4Nwf8/Lb2AMrP4Ufn4RrJkQEAkdxkOZevlXtIhIEZWrXnIjRoygQYMG+Pr6UrJkSdq2bcvOnTtzrJOWlkbv3r0JCgrCx8eH9u3bEx8fn6dFi1wrq9XwxfL9tBq9jPUHz+Lj7sLIdjWY8EiDKweP1LMw5SGY96wteFRpDf+3TMFDRCSP5Cp8LFmyhN69e7Nq1Sp++eUXMjMzueOOO0hOTrav89RTT/Hjjz8ybdo0lixZwtGjR2nXrl2eFy7ybw6cSqbz2FW8Nnsb6VlWmlQIZv5TN9O5YeSVL7McWQ+f3gw7ZoOzG7R6Czp9A54B+Vq7iEhRZjHGmOvd+OTJk5QsWZIlS5Zw8803k5iYSEhICJMmTaJDhw4A7Nixg5iYGFauXEmjRo3+dZ9JSUn4+/uTmJiIn5/f9ZYmxZjVavh61UFGzt1BamY2Xm7OvHB3DA9eLXQYAys/ggVDwZoFJcpCx/FQqk5+li4iUmjl5vv7P/X5SEy0jY0QGGjr9b9+/XoyMzNp0aKFfZ0qVaoQGRl5xfCRnp5Oenp6juJFrtfhMykMmr6RVfvOABBXLoi3OtQkItDryhulnIGZT8KuubZ21bZw7wfg4X/jCxYRKYauO3xYrVYGDBhA48aNqV69OgDHjx/Hzc2NgICAHOuGhoZy/Pjxy+5nxIgRDBs27HrLEAFsZzsmrjnEiJ+2k5KRjaerM0PuqsJDsVE4OV3lzpTDa2DaI5B0BJzd4c43oH4P3c0iInIDXXf46N27N1u2bGH58uX/qYAhQ4YwcOBAezspKYmIiIj/tE8pXo6cTeHZ7zaxYs9pABqWDeTtjjWJCvK+8kZWK6z8EBa+arvMEljedpklvGb+FC0iUoxdV/jo06cPs2fPZunSpZQpU8a+PCwsjIyMDBISEnKc/YiPjycsLOyy+3J3d8fd/TITd4n8C2MMk9ceZvic7ZxPz8LD1Yln76xCt7iyVz/bkXwaZj4Ou3+2tat3gHveB3fffKlbRKS4y1X4MMbQt29fZsyYweLFi4mOjs7xeL169XB1dWXhwoW0b98egJ07d3Lo0CHi4jTbp+Sdc2mZ9Jn0B0t2nQSgXlQJ3ulYi+jgq5ztADi4EqY/CueOgosHtHoT6nbTZRYRkXyUq/DRu3dvJk2axA8//ICvr6+9H4e/vz+enp74+/vTo0cPBg4cSGBgIH5+fvTt25e4uLhrutNF5FqkZmTTY/w61hw4g5uLE4NbVuaRxtE4X+1sh9UKK0bBouFgsiGoou0yS1j1fKtbRERscnWr7ZVuUxw3bhzdu3cHbIOMPf3003z77bekp6fTsmVLPv744ytedvkn3WorV5ORZeWxr9exeOdJfN1dmNSrETXK/MtdKedPwoz/g70Lbe2aneDu98Dd58YXLCJSTOTm+/s/jfNxIyh8yJVkWw39Jv/BnE3H8HB14usesTQo+y+Tux1YDtN7wPnj4OIJd70NdR7SZRYRkTyWb+N8iOQXYwwvzNjMnE3HcHW28OnD9a8ePKzZsOxdWDwCjBWCK8P9E6BkTP4VLSIil6XwIQWeMYY3ftrO5LWHcbLA6M51aFYp5MobnD8B3/WE/Uts7dpdbGc83P6lM6qIiOQLhQ8p8P63aA+fLdsPwMj2NbmrRviVV963xBY8kk+Aq5etb0ftB/KpUhERuRYKH1KgjVuxn3d/2QXAy62rcn/9KwxAZ82GJW/CkrcAAyWr2u5mCamcb7WKiMi1UfiQAmv6+iMM+3EbAANaVOTRJtGXX/HccdvZjgPLbO26XeHON8HtKvO5iIiIwyh8SIE0b8sxBk/fCMCjjaPpf1vFy6+4dxF8/xgknwQ3H2j9PtTsmH+FiohIril8SIGzbPdJ+n27AauB++uX4aXWMZeOMZOVYbvMsuxdwEBoDdtlluAKjihZRERyQeFDCpT1B8/w2Ffryci2cleNMEa0q3lp8PhzPfzQF05stbXrPwot3wBXz/wvWEREck3hQwqMrUcT6T5uLamZ2TSrFML7nerkHDI9IwUWvwErP7KN3eEVBHe9A9XbOa5oERHJNYUPKRD2nTxP1y/WcC4tiwZlSzDmoXq4uTj9tcL+pTCrH5y13XJLjY5w50jwDnZMwSIict0UPsTh/kxI5aHPV3M6OYNqpfz4onsDPN2cbQ+mJsAvL8HvX9nafqWh9Sio1NJh9YqIyH+j8CEOdfJcOg99vpqjiWmUD/Hmq0cb4ufhantw+2yY87RtXhaABj3htqHgoTl/REQKM4UPcZjElEy6frmG/aeSKR3gyTc9YwnycbcNj/7TINg207ZiUAW45wMo29ih9YqISN5Q+BCHSMnI4pHxa9h+LIlgH3cm9owl3M8DNnwL856DtASwOEPj/tDsWXD1cHTJIiKSRxQ+JN+lZ2Xzf1+v5/dDCfh7uvJNz4aUdT4F3wywDRoGEFYT2vwPwms5tFYREcl7Ch+Sr7KyrfT79g+W7T6Fl5sz47rVpcqBSbDwVchMBmd3uGUIxPUFZ308RUSKIv12l3xjtRoGf7eJ+VvjcXNxYuK9/tRZ0BmOrLWtENXY1rdDo5SKiBRpCh+SL4wxvDp7G9///iceTtnMrrWKCnPHQHYGuPnC7cOg3iPg5PTvOxMRkUJN4UPyxahfdjH+twPUtOzl6+Cv8d+6y/ZApTvh7vfAv7RjCxQRkXyj8CE33GdL9zF20Vaed5lOT5e5OCVdGBq91VtQvT38c+4WEREp0hQ+5Ib6ds0hFs2bzny3z4hyOmFbWOP+C0OjBzm2OBERcQiFD7lh5q7dgeXH5/jW7VfbAr8yF4ZGv8OxhYmIiEMpfMgNsXnBROoue55Q5wQATINeWFoMBXdfxxYmIiIOp/AheetcPKen96fGwblggXi3CIIf+BTnaA2NLiIiNgofkjeMgQ2TyJo3hKD0RLKME/MDOnHHk+/h7O7l6OpERKQAUfiQ/+7sQfixP+z7FRdgs7UsE0MH88pjnXF1dXZ0dSIiUsAofMj1s2bDmrGw8DXITCYNN0ZltmdN2AN83bMxHgoeIiJyGQofcn1O7IBZfexDo29wqsZTqY/iWrIiUx6Nw8ddHy0REbk8fUNI7mRlwPJRsPRtsGZi3Hz4wKkr7yfcRESgD1N6xFLC283RVYqISAGm8CHX7sh629mOE9sAyKrQksdOP8iiY66E+rkzsWcsJf08HFykiIgUdAof8u8ykuHXN2DVx2BsQ6Nn3DGSh1eVYfWxs5TwcuWbHrFEBOquFhER+XcKH3J1+xbDrH6QcNDWrtmJzNuH88R3B1h94AQ+7i589WgsFUM1eJiIiFwbhQ+5vNSz8POL8Mc3trZfGbjnfbLLt2DglA0s3HECdxcnvuhWnxpl/B1bq4iIFCoKH3KpbbPgp2fgfLyt3aAXtBiKcfPhpZlb+HHjUVycLIx5qB6x5TQ5nIiI5I7Ch/zlXLwtdGyfZWsHVYR7P4SoOIwxjJy3g0mrD2GxwPuda3NLlZKOrVdERAolhQ+xD43O/OchLQEsztBkANw8GFxtd698vHgvny7ZB8CI+2rQumYpx9UrIiKFmsJHcXf2APw4APZdmPY+vBbc+z8Ir2lf5auVB3h7/k4AXrgrhs4NI/O/ThERKTIUPoorazas/hQWvQaZKeDiAbc8D416g/NfH4sZfxzh5R+2AtDv1gr0urmcoyoWEZEiQuGjODqxHX7oA3+us7WjmsC9H0BQ+Ryr/bz1OM9M2wRA95vK8tTtlfK7UhERKYIUPoqTrAxY/h4sfQesmeDuB7cPg7rdwckpx6or9pyiz6Q/yLYa2tctw8utq2KxWBxTt4iIFCkKH8XFkXUwq699aHQqtYK73wX/0pes+vuhs/T6ah0Z2VZaVgvlzfY1cHJS8BARkbzh9O+r5LR06VLuueceSpUqhcViYebMmTkeN8bw8ssvEx4ejqenJy1atGD37t15Va/kVkYyzHsePm9hCx5ewdDhS3jg28sGj+3Hkuj+5RpSMrJpWjGYDx6og4tzrj8mIiIiV5Trb5Xk5GRq1arFRx99dNnH33rrLT744APGjBnD6tWr8fb2pmXLlqSlpf3nYiWX9v4KH8fBqo8AAzU7Q5+1UL09XOYSyv5TyTz8xRqS0rKoF1WCTx+uh7uLc/7XLSIiRVquL7u0atWKVq1aXfYxYwzvv/8+L774Im3atAHgq6++IjQ0lJkzZ9K5c+f/Vq1cmysMjU7F26+4ydGEVB76fDWnzqcTE+7Hl90b4OWmq3IiIpL38vR8+v79+zl+/DgtWrSwL/P39yc2NpaVK1dedpv09HSSkpJy/Mh/sG0WfBR7IXhYoOFj0HvVVYPHqfPpPPTFav5MSKVcsDdf92iIv6dr/tUsIiLFSp7+aXv8+HEAQkNDcywPDQ21P/ZPI0aMYNiwYXlZRvF07viFodF/tLWDKkKb/0Fko6tulpiaSdcv1rDvZDKl/D34umcswT7u+VCwiIgUVw7vSThkyBASExPtP4cPH3Z0SYWLMfD71/BRQ1vwcHKBps/A48v/NXikZmTTY/xath1LItjHjW96xlI6wDOfChcRkeIqT898hIWFARAfH094eLh9eXx8PLVr177sNu7u7ri76y/t63JmP8weAPsW29rhtW1nO8Jq/Oum6VnZ/N8361l38Cy+Hi589Wgs5UJ8bmS1IiIiQB6f+YiOjiYsLIyFCxfalyUlJbF69Wri4uLy8qmKN2s2rPwIPrnJFjxcPOD2V6HnwmsKHlnZVgZM3sDSXSfxdHVm/CMNqFrK78bXLSIiwnWc+Th//jx79uyxt/fv38+GDRsIDAwkMjKSAQMG8Prrr1OxYkWio6N56aWXKFWqFG3bts3Luouv+G22wcL+ZWj0K7FaDUO+38zcLcdxc3ZibNd61IsKvIEFi4iI5JTr8LFu3TpuueUWe3vgwIEAdOvWjfHjxzN48GCSk5N57LHHSEhIoEmTJsybNw8PD4+8q7q4Wvcl/DT4b0Ojvwp1u10yNPqVGGN4bc42pq0/gpMFPnigDk0rhtzgokVERHKyGGOMo4v4u6SkJPz9/UlMTMTPT5cCANtllp9fhFUf29qVWkHr98CvVK528/6CXby/wDba7Dsda9GhXpm8rlRERIqp3Hx/axSpgi4tCb7rCbvn29q3vgRNn77sCKVX88Xy/fbg8co9VRU8RETEYRQ+CrKEQzCpk21OFhdPuG8MVGub691MXXuY12bbJpR7+vZKdG8cnceFioiIXDuFj4Lq8FqY/AAknwSfUNtEcKXr5Xo3czYd47nvNwHQq2k0fW6tkNeVioiI5IrCR0G0eTrMfBKy0223zj4wGfxzf5lk8c4TDJjyB1YDnRtE8PxdMVhyeblGREQkryl8FCTGwJI3YfEIW7vyXdDuM3DP/eBfaw+c4fFv1pOZbWhdM5zh99VQ8BARkQJB4aOgyEyDH3rDlum29k39oMUr4JT7Ke23/JnIo+PWkpZp5ZbKIbx3f22cnRQ8RESkYFD4KAjOn4DJD8KRtba5WVqPgrpdr2tXe06cp+uXaziXnkXD6EA+7lIPNxeHT+EjIiJip/DhaPFbbXe0JB4GjwDo9DVE33xduzp8JoWHPl/NmeQMapT254tu9fF0y/2ZExERkRtJ4cORdv0M0x+BjPMQWB66TLvmYdL/6URSGg99sZrjSWlUKOnDhEcb4uvhmscFi4iI/HcKH45gDKz+FOYPAWOFsk3h/q/A6/rmWElIyeDhL9Zw8HQKZUp48k2PWAK93fK4aBERkbyh8JHfsjNh7mDbPC0AdR6Gu98Dl+sLC+fTs+g+bi07489R0tediT1jCfPXPDoiIlJwKXzkp9QEmNYd9v0KWOCO1yCuT66HSr8oLTObx75ax4bDCQR4ufJ1j1iigrzzsmIREZE8p/CRX87ss3UsPbULXL2h/edQ5a7r3l1mtpU+k/7gt72n8XZzZsIjDakc5puHBYuIiNwYCh/54eBvMLkLpJ4Bv9K2EUvDa1737qxWw6BpG1mwPR43Fyc+79aAWhEBeVeviIjIDaTwcaNtmASz+oE1E0rVtc3R4ht23bszxjB01lZmbjiKi5OFT7rUJa58UB4WLCIicmMpfNwoVisseg2Wv2drV20DbceAm9d/2u3b83fy9aqDWCzw7v21uC0mNA+KFRERyT8KHzdCRjLM+D/Y/qOtffMgaP48OF3/SKOHTqfwxk/bmbf1OACvt61Om9ql86JaERGRfKXwkdeSjsG3neHYBnB2g3s/hFqdr3t359Oz+OjXPXyxbD8Z2VacLPD8XTF0iY3Ku5pFRETykcJHXjq6Ab59AM4dBa8g6DwJIhtd166yrYbv1h/hrfk7OXU+HYAmFYJ5qXVV3dUiIiKFmsJHXtk+G77vBZkpEFLFdkdLYPR17Wr1vtO8OnsbW48mARAd7M0Ld8VwW0xJLNc5JoiIiEhBofDxXxkDK0bDglcAA+VvhY7jwcM/17s6fCaFEXO389NmW78OXw8X+t9Wka5xZTUzrYiIFBkKH/9FVgbMfgo2fGNrN+gFd44E59y9refTs/j41z18vnw/GVm2fh2dG0by9O2VCPJxvwGFi4iIOI7Cx/VKOQNTHoaDy8HiBHe+CbGP5WoXVqvhu99t/TpOnrP167ipfBAvta5KTLjfjahaRETE4RQ+rsep3TDpftuQ6W6+tsssFVvkahdrD5zh1R+3sfnPRACigrx44a4Ybq8aqn4dIiJSpCl85Na+xTC1K6QlQkAkPDAFQqte8+aHz6Qwct4O5mw6BoCvuwt9b6tAt5vK4u7ifIOKFhERKTgUPnJj/XiY8zRYsyAiFjpNBJ+Qa9o0OT2LTxbvZeyyfWRkWbFYoHODSJ6+oxLB6tchIiLFiMLHtbBmwy8vw8r/2do17rcNHubq8e+bWg3f//Enb83bwYkL/ToalQvk5dbVqFpK/TpERKT4Ufj4N+nn4LuesGuerX3Li3DzM3AN/TLWHTjDq7O3semIrV9HZKAXz98VQ8tq6tchIiLFl8LH1SQctg2VHr8FXDyg7SdQvd2/bvZnQioj5+7gx41HAfBxd6HPrRV4pLH6dYiIiCh8XMmRdbah0pNPgHdJ24ilZepddZOUjCzGLN7Lp0v3kX6hX0en+hE8fUdlQnzVr0NERAQUPi5vy/cw8wnISoPQ6rbgERBxxdWtVsPMDX/y5rwdxCfZ+nU0jA7k5dZVqV469yOdioiIFGUKH39nDCx9G34dbmtXuhPafw7uV57Ibf3Bs7w6exsbDycAEBHoyfOtYrizepj6dYiIiFyGwsdFmWkwqy9snmprx/WB218Fp8v30TiakMqb83bwwwZbvw5vN2d631qBRxtH4+Gqfh0iIiJXovABcP4kTOkCh1eDkwvc/S7U637ZVVMyshizZB9jl+4lLdPWr6NjvTI807IyJX3//dZbERGR4k7hI34bfNsJEg7ZZqK9/2so1+yS1axWw6yNRxk5dwfHk9IAaFg2kJfvUb8OERGR3Cje4WP3ApjWHTLOQWA5eHAqBFe8ZLU/Dp1l2I/b2HChX0fpAE+evyuGu2qoX4eIiEhuFd/wsXoszHsWjBWimkCnr8ErMMcqxxJTeWveTmb88ScAXm7O9L6lAj2aqF+HiIjI9Sp+4SM7C+Y9B2s/s7XrPAR3jwIXN/sqqRnZjF26jzFL9pKamY3FAh3qlmFQy8qU9FO/DhERkf+ieIWPtETbZZa9iwAL3D4MbupnHyrdmL/6dRxLtPXrqB9VgqH3VKNGGfXrEBERyQvFJ3yc2W8bKv3kDnD1gnafQUxr+8MbDifw6o9b+f1QAmDr1zHkrircXSNc/TpERETyUPEJH6ln4OwB8C0FD06G8FoAHE9M4615O/j+b/06nmxenp5Ny6lfh4iIyA3gdKN2/NFHH1G2bFk8PDyIjY1lzZo1N+qprk3petB5IvRaBOG1SMvM5oOFu7nlncX24NG+bhl+faY5fW6tqOAhIiJyg9yQMx9Tpkxh4MCBjBkzhtjYWN5//31atmzJzp07KVmy5I14ymtToQXGGH7ceJSRP23n6IV+HfWiSvBy66rUighwXG0iIiLFhMUYY/J6p7GxsTRo0ID//e9/AFitViIiIujbty/PPffcVbdNSkrC39+fxMRE/Pz88rSujYcTeHX2NtYfPAtAKX8Pnrsrhntqql+HiIjIf5Gb7+88P/ORkZHB+vXrGTJkiH2Zk5MTLVq0YOXKlXn9dNds4fZ4ekxYB4CnqzNPNC9Pr6bl8HTT5RUREZH8lOfh49SpU2RnZxMaGppjeWhoKDt27Lhk/fT0dNLT0+3tpKSkvC4JgMYVgokM9KJ+VAkG3VmZcH/PG/I8IiIicnUOv9tlxIgRDBs27IY/j4erMz/1b4qPu8NfsoiISLGW53e7BAcH4+zsTHx8fI7l8fHxhIWFXbL+kCFDSExMtP8cPnw4r0uyU/AQERFxvDwPH25ubtSrV4+FCxfal1mtVhYuXEhcXNwl67u7u+Pn55fjR0RERIquG3IqYODAgXTr1o369evTsGFD3n//fZKTk3nkkUduxNOJiIhIIXJDwkenTp04efIkL7/8MsePH6d27drMmzfvkk6oIiIiUvzckHE+/osbOc6HiIiI3Bi5+f6+YcOri4iIiFyOwoeIiIjkK4UPERERyVcKHyIiIpKvFD5EREQkXyl8iIiISL5S+BAREZF8pfAhIiIi+UrhQ0RERPJVgZvm9eKAq0lJSQ6uRERERK7Vxe/taxk4vcCFj3PnzgEQERHh4EpEREQkt86dO4e/v/9V1ylwc7tYrVaOHj2Kr68vFovlqusmJSURERHB4cOHNQ+Mg+gYOJ6OQcGg4+B4OgaOZYzh3LlzlCpVCienq/fqKHBnPpycnChTpkyutvHz89MHzcF0DBxPx6Bg0HFwPB0Dx/m3Mx4XqcOpiIiI5CuFDxEREclXhTp8uLu7M3ToUNzd3R1dSrGlY+B4OgYFg46D4+kYFB4FrsOpiIiIFG2F+syHiIiIFD4KHyIiIpKvFD5EREQkXyl8iIiISL4qtOHjo48+omzZsnh4eBAbG8uaNWscXVKRNWLECBo0aICvry8lS5akbdu27Ny5M8c6aWlp9O7dm6CgIHx8fGjfvj3x8fEOqrjoGzlyJBaLhQEDBtiX6Rjkjz///JOHHnqIoKAgPD09qVGjBuvWrbM/bozh5ZdfJjw8HE9PT1q0aMHu3bsdWHHRkp2dzUsvvUR0dDSenp6UL1+e1157Lcd8IjoGhYAphCZPnmzc3NzMl19+abZu3Wp69eplAgICTHx8vKNLK5Jatmxpxo0bZ7Zs2WI2bNhg7rrrLhMZGWnOnz9vX+fxxx83ERERZuHChWbdunWmUaNG5qabbnJg1UXXmjVrTNmyZU3NmjVN//797ct1DG68M2fOmKioKNO9e3ezevVqs2/fPjN//nyzZ88e+zojR440/v7+ZubMmWbjxo3m3nvvNdHR0SY1NdWBlRcdw4cPN0FBQWb27Nlm//79Ztq0acbHx8eMHj3avo6OQcFXKMNHw4YNTe/eve3t7OxsU6pUKTNixAgHVlV8nDhxwgBmyZIlxhhjEhISjKurq5k2bZp9ne3btxvArFy50lFlFknnzp0zFStWNL/88otp1qyZPXzoGOSPZ5991jRp0uSKj1utVhMWFmbefvtt+7KEhATj7u5uvv322/wosci7++67zaOPPppjWbt27UyXLl2MMToGhUWhu+ySkZHB+vXradGihX2Zk5MTLVq0YOXKlQ6srPhITEwEIDAwEID169eTmZmZ45hUqVKFyMhIHZM81rt3b+6+++4c7zXoGOSXWbNmUb9+fTp27EjJkiWpU6cOn332mf3x/fv3c/z48RzHwd/fn9jYWB2HPHLTTTexcOFCdu3aBcDGjRtZvnw5rVq1AnQMCosCN7Hcvzl16hTZ2dmEhobmWB4aGsqOHTscVFXxYbVaGTBgAI0bN6Z69eoAHD9+HDc3NwICAnKsGxoayvHjxx1QZdE0efJkfv/9d9auXXvJYzoG+WPfvn188sknDBw4kOeff561a9fSr18/3Nzc6Natm/29vtzvJx2HvPHcc8+RlJRElSpVcHZ2Jjs7m+HDh9OlSxcAHYNCotCFD3Gs3r17s2XLFpYvX+7oUoqVw4cP079/f3755Rc8PDwcXU6xZbVaqV+/Pm+88QYAderUYcuWLYwZM4Zu3bo5uLriYerUqUycOJFJkyZRrVo1NmzYwIABAyhVqpSOQSFS6C67BAcH4+zsfEkv/vj4eMLCwhxUVfHQp08fZs+eza+//kqZMmXsy8PCwsjIyCAhISHH+jomeWf9+vWcOHGCunXr4uLigouLC0uWLOGDDz7AxcWF0NBQHYN8EB4eTtWqVXMsi4mJ4dChQwD291q/n26cQYMG8dxzz9G5c2dq1KjBww8/zFNPPcWIESMAHYPCotCFDzc3N+rVq8fChQvty6xWKwsXLiQuLs6BlRVdxhj69OnDjBkzWLRoEdHR0Tker1evHq6urjmOyc6dOzl06JCOSR657bbb2Lx5Mxs2bLD/1K9fny5dutj/rWNw4zVu3PiS28x37dpFVFQUANHR0YSFheU4DklJSaxevVrHIY+kpKTg5JTzq8vZ2Rmr1QroGBQaju7xej0mT55s3N3dzfjx4822bdvMY489ZgICAszx48cdXVqR9MQTTxh/f3+zePFic+zYMftPSkqKfZ3HH3/cREZGmkWLFpl169aZuLg4ExcX58Cqi76/3+1ijI5BflizZo1xcXExw4cPN7t37zYTJ040Xl5e5ptvvrGvM3LkSBMQEGB++OEHs2nTJtOmTRvd5pmHunXrZkqXLm2/1fb77783wcHBZvDgwfZ1dAwKvkIZPowx5sMPPzSRkZHGzc3NNGzY0KxatcrRJRVZwGV/xo0bZ18nNTXVPPnkk6ZEiRLGy8vL3HfffebYsWOOK7oY+Gf40DHIHz/++KOpXr26cXd3N1WqVDFjx47N8bjVajUvvfSSCQ0NNe7u7ua2224zO3fudFC1RU9SUpLp37+/iYyMNB4eHqZcuXLmhRdeMOnp6fZ1dAwKPosxfxsWTkREROQGK3R9PkRERKRwU/gQERGRfKXwISIiIvlK4UNERETylcKHiIiI5CuFDxEREclXCh8iIiKSrxQ+RMQhXnnlFWrXrl1knkdErp3Ch4iIiOQrhQ8RERHJVwofIsWY1WrlrbfeokKFCri7uxMZGcnw4cM5cOAAFouFyZMnc9NNN+Hh4UH16tVZsmSJfdvx48cTEBCQY38zZ87EYrFcdy2vvvoqZcqUwd3dndq1azNv3rwc6zz77LNUqlQJLy8vypUrx0svvURmZmaOdUaOHEloaCi+vr706NGDtLS066pHRG4chQ+RYmzIkCGMHDmSl156iW3btjFp0iRCQ0Ptjw8aNIinn36aP/74g7i4OO655x5Onz59Q2oZPXo07777Lu+88w6bNm2iZcuW3Hvvvezevdu+jq+vL+PHj2fbtm2MHj2azz77jFGjRtkfnzp1Kq+88gpvvPEG69atIzw8nI8//viG1Csi/4GjZ7YTEcdISkoy7u7u5rPPPrvksf379xvAjBw50r4sMzPTlClTxrz55pvGGGPGjRtn/P39c2w3Y8YMc62/VoYOHWpq1aplb5cqVcoMHz48xzoNGjQwTz755BX38fbbb5t69erZ23FxcZesHxsbm+N5RMTxdOZDpJjavn076enp3HbbbVdcJy4uzv5vFxcX6tevz/bt2/O8lqSkJI4ePUrjxo1zLG/cuHGO55syZQqNGzcmLCwMHx8fXnzxRQ4dOmR/fPv27cTGxl7xNYhIwaDwIVJMeXp6/qftnZycMMbkWPbP/hd5aeXKlXTp0oW77rqL2bNn88cff/DCCy+QkZFxw55TRG4MhQ+RYqpixYp4enqycOHCK66zatUq+7+zsrJYv349MTExAISEhHDu3DmSk5Pt62zYsOG6avHz86NUqVKsWLEix/IVK1ZQtWpVAH777TeioqJ44YUXqF+/PhUrVuTgwYM51o+JiWH16tVXfA0iUjC4OLoAEXEMDw8Pnn32WQYPHoybmxuNGzfm5MmTbN261X4p5qOPPqJixYrExMQwatQozp49y6OPPgpAbGwsXl5ePP/88/Tr14/Vq1czfvz4665n0KBBDB06lPLly1O7dm3GjRvHhg0bmDhxImALS4cOHWLy5Mk0aNCAOXPmMGPGjBz76N+/P927d6d+/fo0btyYiRMnsnXrVsqVK3fddYnIDeDoTici4jjZ2dnm9ddfN1FRUcbV1dVERkaaN954w97hdNKkSaZhw4bGzc3NVK1a1SxatCjH9jNmzDAVKlQwnp6epnXr1mbs2LHX3eE0OzvbvPLKK6Z06dLG1dXV1KpVy8ydOzfHNoMGDTJBQUHGx8fHdOrUyYwaNeqSTq/Dhw83wcHBxsfHx3Tr1s0MHjxYHU5FChiLMf+4aCsixd6BAweIjo7mjz/+0NDkIpLn1OdDRERE8pXCh4jcENWqVcPHx+eyPxf7cYhI8aTLLiJyQxw8ePCKt95eHP5cRIonhQ8RERHJV7rsIiIiIvlK4UNERETylcKHiIiI5CuFDxEREclXCh8iIiKSrxQ+REREJF8pfIiIiEi+UvgQERGRfPX/5xqNS9D6EggAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "csv = '../codecarbon/data/hardware/cpu_load_profiling/E3-1240/compare_cpu_load_and_RAPL-some_cores-Intel(R)_Xeon(R)_CPU_E3-1240_V2_@_3.40GHz-2025-01-11.csv'\n",
    "df_some_cores = get_df(csv)\n",
    "plot(df_some_cores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Side notes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have to find what the real TDP of CPU is. Because for the Intel(R) Xeon(R) CPU E5-2620 v3 @ 2.40GHz, the TDP is 85 W, but the real TDP seems to be 60 W.\n",
    "\n",
    "```sh\n",
    "$ stress-ng --cpu 0 --cpu-method matrixprod --metrics-brief --rapl --perf -t 60s\n",
    "stress-ng: info:  [9573] setting to a 1 min run per stressor\n",
    "stress-ng: info:  [9573] dispatching hogs: 24 cpu\n",
    "stress-ng: metrc: [9573] stressor       bogo ops real time  usr time  sys time   bogo ops/s     bogo ops/s\n",
    "stress-ng: metrc: [9573]                           (secs)    (secs)    (secs)   (real time) (usr+sys time)\n",
    "stress-ng: metrc: [9573] cpu              614145     60.00   1439.79      0.04     10235.00         426.54\n",
    "stress-ng: info:  [9573] Cannot read perf counters, do not have CAP_SYS_ADMIN capability or /proc/sys/kernel/perf_event_paranoid is set too high (4)\n",
    "stress-ng: info:  [9573] cpu:\n",
    "stress-ng: info:  [9573]  dram                    6.09 W\n",
    "stress-ng: info:  [9573]  pkg-0                  51.78 W\n",
    "stress-ng: info:  [9573]  pkg-1                  54.41 W\n",
    "stress-ng: info:  [9573] skipped: 0\n",
    "stress-ng: info:  [9573] passed: 24: cpu (24)\n",
    "stress-ng: info:  [9573] failed: 0\n",
    "stress-ng: info:  [9573] metrics untrustworthy: 0\n",
    "stress-ng: info:  [9573] successful run completed in 1 min\n",
    "```\n",
    "\n",
    "```sh\n",
    "ubuntu@sd-175544:~/codecarbon$ hatch run python examples/intel_rapl_show.py\n",
    "Detailed RAPL Domain Information:\n",
    "{\n",
    "  \"intel-rapl:1\": {\n",
    "    \"name\": \"intel-rapl:1\",\n",
    "    \"files\": {\n",
    "      \"uevent\": \"\",\n",
    "      \"energy_uj\": \"22464335801\",\n",
    "      \"enabled\": \"0\",\n",
    "      \"constraint_1_max_power_uw\": \"170000000\",\n",
    "      \"constraint_1_time_window_us\": \"7808\",\n",
    "      \"constraint_1_power_limit_uw\": \"102000000\",\n",
    "      \"constraint_0_time_window_us\": \"9994240\",\n",
    "      \"constraint_1_name\": \"short_term\",\n",
    "      \"constraint_0_power_limit_uw\": \"85000000\",\n",
    "      \"constraint_0_name\": \"long_term\",\n",
    "      \"name\": \"package-1\",\n",
    "      \"constraint_0_max_power_uw\": \"85000000\",\n",
    "      \"max_energy_range_uj\": \"262143328850\"\n",
    "    },\n",
    "    \"subdomain_details\": {}\n",
    "  },\n",
    "  \"intel-rapl:0\": {\n",
    "    \"name\": \"intel-rapl:0\",\n",
    "    \"files\": {\n",
    "      \"uevent\": \"\",\n",
    "      \"energy_uj\": \"23712361659\",\n",
    "      \"enabled\": \"0\",\n",
    "      \"constraint_1_max_power_uw\": \"170000000\",\n",
    "      \"constraint_1_time_window_us\": \"7808\",\n",
    "      \"constraint_1_power_limit_uw\": \"102000000\",\n",
    "      \"constraint_0_time_window_us\": \"9994240\",\n",
    "      \"constraint_1_name\": \"short_term\",\n",
    "      \"constraint_0_power_limit_uw\": \"85000000\",\n",
    "      \"constraint_0_name\": \"long_term\",\n",
    "      \"name\": \"package-0\",\n",
    "      \"constraint_0_max_power_uw\": \"85000000\",\n",
    "      \"max_energy_range_uj\": \"262143328850\"\n",
    "    },\n",
    "    \"subdomain_details\": {}\n",
    "  }\n",
    "}\n",
    "\n",
    "Potential RAM Domains:\n",
    "Available Power Domains:\n",
    "Starting Power Monitoring:\n",
    "Power Consumption: 12.82 Watts\n",
    "Power Consumption: 14.27 Watts\n",
    "Power Consumption: 14.43 Watts\n",
    "```\n",
    "\n",
    "```sh\n",
    "ubuntu@sd-175544:~/codecarbon$ lscpu\n",
    "Architecture:             x86_64\n",
    "  CPU op-mode(s):         32-bit, 64-bit\n",
    "  Address sizes:          46 bits physical, 48 bits virtual\n",
    "  Byte Order:             Little Endian\n",
    "CPU(s):                   24\n",
    "  On-line CPU(s) list:    0-23\n",
    "Vendor ID:                GenuineIntel\n",
    "  Model name:             Intel(R) Xeon(R) CPU E5-2620 v3 @ 2.40GHz\n",
    "    CPU family:           6\n",
    "    Model:                63\n",
    "    Thread(s) per core:   2\n",
    "    Core(s) per socket:   6\n",
    "    Socket(s):            2\n",
    "    Stepping:             2\n",
    "    CPU(s) scaling MHz:   41%\n",
    "    CPU max MHz:          3200.0000\n",
    "    CPU min MHz:          1200.0000\n",
    "    BogoMIPS:             4799.72\n",
    "    Flags:                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_\n",
    "                          tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pd\n",
    "                          cm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm cpuid_fault epb pti ssbd ibrs ibpb stibp tpr_shadow fle\n",
    "                          xpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm xsaveopt cqm_llc cqm_occup_llc dtherm ida arat pln pts vnmi md_clear flush_\n",
    "                          l1d\n",
    "Virtualization features:\n",
    "  Virtualization:         VT-x\n",
    "Caches (sum of all):\n",
    "  L1d:                    384 KiB (12 instances)\n",
    "  L1i:                    384 KiB (12 instances)\n",
    "  L2:                     3 MiB (12 instances)\n",
    "  L3:                     30 MiB (2 instances)\n",
    "NUMA:\n",
    "  NUMA node(s):           2\n",
    "  NUMA node0 CPU(s):      0,2,4,6,8,10,12,14,16,18,20,22\n",
    "  NUMA node1 CPU(s):      1,3,5,7,9,11,13,15,17,19,21,23\n",
    "Vulnerabilities:\n",
    "  Gather data sampling:   Not affected\n",
    "  Itlb multihit:          KVM: Mitigation: VMX disabled\n",
    "  L1tf:                   Mitigation; PTE Inversion; VMX conditional cache flushes, SMT vulnerable\n",
    "  Mds:                    Mitigation; Clear CPU buffers; SMT vulnerable\n",
    "  Meltdown:               Mitigation; PTI\n",
    "  Mmio stale data:        Mitigation; Clear CPU buffers; SMT vulnerable\n",
    "  Reg file data sampling: Not affected\n",
    "  Retbleed:               Not affected\n",
    "  Spec rstack overflow:   Not affected\n",
    "  Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl\n",
    "  Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization\n",
    "  Spectre v2:             Mitigation; Retpolines; IBPB conditional; IBRS_FW; STIBP conditional; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected\n",
    "  Srbds:                  Not affected\n",
    "  Tsx async abort:        Not affected\n",
    "```\n",
    "\n",
    "```sh\n",
    "ubuntu@sd-175544:~/codecarbon$ hatch run python\n",
    "Python 3.12.3 (main, Nov  6 2024, 18:32:19) [GCC 13.2.0] on linux\n",
    "Type \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n",
    ">>> from cpuinfo import get_cpu_info\n",
    ">>> get_cpu_info()\n",
    "{'python_version': '3.12.3.final.0 (64 bit)', 'cpuinfo_version': [9, 0, 0], 'cpuinfo_version_string': '9.0.0', 'arch': 'X86_64', 'bits': 64, 'count': 24, 'arch_string_raw': 'x86_64', 'vendor_id_raw': 'GenuineIntel', 'brand_raw': 'Intel(R) Xeon(R) CPU E5-2620 v3 @ 2.40GHz', 'hz_advertised_friendly': '2.4000 GHz', 'hz_actual_friendly': '2.3737 GHz', 'hz_advertised': [2400000000, 0], 'hz_actual': [2373723000, 0], 'stepping': 2, 'model': 63, 'family': 6, 'flags': ['abm', 'acpi', 'aes', 'aperfmperf', 'apic', 'arat', 'arch_perfmon', 'avx', 'avx2', 'bmi1', 'bmi2', 'bts', 'clflush', 'cmov', 'constant_tsc', 'cpuid', 'cpuid_fault', 'cqm', 'cqm_llc', 'cqm_occup_llc', 'cx16', 'cx8', 'dca', 'de', 'ds_cpl', 'dtes64', 'dtherm', 'dts', 'epb', 'ept', 'ept_ad', 'erms', 'est', 'f16c', 'flexpriority', 'flush_l1d', 'fma', 'fpu', 'fsgsbase', 'fxsr', 'ht', 'ibpb', 'ibrs', 'ida', 'invpcid', 'lahf_lm', 'lm', 'mca', 'mce', 'md_clear', 'mmx', 'monitor', 'movbe', 'msr', 'mtrr', 'nonstop_tsc', 'nopl', 'nx', 'osxsave', 'pae', 'pat', 'pbe', 'pcid', 'pclmulqdq', 'pdcm', 'pdpe1gb', 'pebs', 'pge', 'pln', 'pni', 'popcnt', 'pqm', 'pse', 'pse36', 'pti', 'pts', 'rdrand', 'rdrnd', 'rdtscp', 'rep_good', 'sdbg', 'sep', 'smep', 'smx', 'ss', 'ssbd', 'sse', 'sse2', 'sse4_1', 'sse4_2', 'ssse3', 'stibp', 'syscall', 'tm', 'tm2', 'tpr_shadow', 'tsc', 'tsc_adjust', 'tsc_deadline_timer', 'tscdeadline', 'vme', 'vmx', 'vnmi', 'vpid', 'x2apic', 'xsave', 'xsaveopt', 'xtopology', 'xtpr'], 'l3_cache_size': 15728640, 'l2_cache_size': 3145728, 'l1_data_cache_size': 393216, 'l1_instruction_cache_size': 393216, 'l2_cache_line_size': 256, 'l2_cache_associativity': 6}\n",
    ">>>\n",
    "```\n",
    "\n",
    "Is NUMA node(s) giving the number of physical CPU?\n",
    "\n",
    "```sh\n",
    "ubuntu@sd-175544:~/codecarbon$ sudo dmidecode -t 4\n",
    "# dmidecode 3.5\n",
    "Getting SMBIOS data from sysfs.\n",
    "SMBIOS 2.8 present.\n",
    "\n",
    "Handle 0x0400, DMI type 4, 42 bytes\n",
    "Processor Information\n",
    "\tSocket Designation: CPU1\n",
    "\tType: Central Processor\n",
    "\tFamily: Xeon\n",
    "\tManufacturer: Intel\n",
    "\tID: F2 06 03 00 FF FB EB BF\n",
    "\tSignature: Type 0, Family 6, Model 63, Stepping 2\n",
    "\tFlags:\n",
    "\t\tFPU (Floating-point unit on-chip)\n",
    "\t\tVME (Virtual mode extension)\n",
    "\t\tDE (Debugging extension)\n",
    "\t\tPSE (Page size extension)\n",
    "\t\tTSC (Time stamp counter)\n",
    "\t\tMSR (Model specific registers)\n",
    "\t\tPAE (Physical address extension)\n",
    "\t\tMCE (Machine check exception)\n",
    "\t\tCX8 (CMPXCHG8 instruction supported)\n",
    "\t\tAPIC (On-chip APIC hardware supported)\n",
    "\t\tSEP (Fast system call)\n",
    "\t\tMTRR (Memory type range registers)\n",
    "\t\tPGE (Page global enable)\n",
    "\t\tMCA (Machine check architecture)\n",
    "\t\tCMOV (Conditional move instruction supported)\n",
    "\t\tPAT (Page attribute table)\n",
    "\t\tPSE-36 (36-bit page size extension)\n",
    "\t\tCLFSH (CLFLUSH instruction supported)\n",
    "\t\tDS (Debug store)\n",
    "\t\tACPI (ACPI supported)\n",
    "\t\tMMX (MMX technology supported)\n",
    "\t\tFXSR (FXSAVE and FXSTOR instructions supported)\n",
    "\t\tSSE (Streaming SIMD extensions)\n",
    "\t\tSSE2 (Streaming SIMD extensions 2)\n",
    "\t\tSS (Self-snoop)\n",
    "\t\tHTT (Multi-threading)\n",
    "\t\tTM (Thermal monitor supported)\n",
    "\t\tPBE (Pending break enabled)\n",
    "\tVersion: Intel(R) Xeon(R) CPU E5-2620 v3 @ 2.40GHz\n",
    "\tVoltage: 1.3 V\n",
    "\tExternal Clock: 8000 MHz\n",
    "\tMax Speed: 4000 MHz\n",
    "\tCurrent Speed: 2400 MHz\n",
    "\tStatus: Populated, Enabled\n",
    "\tUpgrade: Socket LGA2011-3\n",
    "\tL1 Cache Handle: 0x0700\n",
    "\tL2 Cache Handle: 0x0701\n",
    "\tL3 Cache Handle: 0x0702\n",
    "\tSerial Number: Not Specified\n",
    "\tAsset Tag: Not Specified\n",
    "\tPart Number: Not Specified\n",
    "\tCore Count: 6\n",
    "\tCore Enabled: 6\n",
    "\tThread Count: 12\n",
    "\tCharacteristics:\n",
    "\t\t64-bit capable\n",
    "\t\tMulti-Core\n",
    "\t\tHardware Thread\n",
    "\t\tExecute Protection\n",
    "\t\tEnhanced Virtualization\n",
    "\t\tPower/Performance Control\n",
    "\n",
    "Handle 0x0401, DMI type 4, 42 bytes\n",
    "Processor Information\n",
    "\tSocket Designation: CPU2\n",
    "\tType: Central Processor\n",
    "\tFamily: Xeon\n",
    "\tManufacturer: Intel\n",
    "\tID: F2 06 03 00 FF FB EB BF\n",
    "\tSignature: Type 0, Family 6, Model 63, Stepping 2\n",
    "\tFlags:\n",
    "\t\tFPU (Floating-point unit on-chip)\n",
    "\t\tVME (Virtual mode extension)\n",
    "\t\tDE (Debugging extension)\n",
    "\t\tPSE (Page size extension)\n",
    "\t\tTSC (Time stamp counter)\n",
    "\t\tMSR (Model specific registers)\n",
    "\t\tPAE (Physical address extension)\n",
    "\t\tMCE (Machine check exception)\n",
    "\t\tCX8 (CMPXCHG8 instruction supported)\n",
    "\t\tAPIC (On-chip APIC hardware supported)\n",
    "\t\tSEP (Fast system call)\n",
    "\t\tMTRR (Memory type range registers)\n",
    "\t\tPGE (Page global enable)\n",
    "\t\tMCA (Machine check architecture)\n",
    "\t\tCMOV (Conditional move instruction supported)\n",
    "\t\tPAT (Page attribute table)\n",
    "\t\tPSE-36 (36-bit page size extension)\n",
    "\t\tCLFSH (CLFLUSH instruction supported)\n",
    "\t\tDS (Debug store)\n",
    "\t\tACPI (ACPI supported)\n",
    "\t\tMMX (MMX technology supported)\n",
    "\t\tFXSR (FXSAVE and FXSTOR instructions supported)\n",
    "\t\tSSE (Streaming SIMD extensions)\n",
    "\t\tSSE2 (Streaming SIMD extensions 2)\n",
    "\t\tSS (Self-snoop)\n",
    "\t\tHTT (Multi-threading)\n",
    "\t\tTM (Thermal monitor supported)\n",
    "\t\tPBE (Pending break enabled)\n",
    "\tVersion: Intel(R) Xeon(R) CPU E5-2620 v3 @ 2.40GHz\n",
    "\tVoltage: 1.3 V\n",
    "\tExternal Clock: 8000 MHz\n",
    "\tMax Speed: 4000 MHz\n",
    "\tCurrent Speed: 2400 MHz\n",
    "\tStatus: Populated, Enabled\n",
    "\tUpgrade: Socket LGA2011-3\n",
    "\tL1 Cache Handle: 0x0703\n",
    "\tL2 Cache Handle: 0x0704\n",
    "\tL3 Cache Handle: 0x0705\n",
    "\tSerial Number: Not Specified\n",
    "\tAsset Tag: Not Specified\n",
    "\tPart Number: Not Specified\n",
    "\tCore Count: 6\n",
    "\tCore Enabled: 6\n",
    "\tThread Count: 12\n",
    "\tCharacteristics:\n",
    "\t\t64-bit capable\n",
    "\t\tMulti-Core\n",
    "\t\tHardware Thread\n",
    "\t\tExecute Protection\n",
    "\t\tEnhanced Virtualization\n",
    "\t\tPower/Performance Control\n",
    "```\n",
    "\n",
    "For the AMD EPYC 8024P 8-Core Processor, the TDP is 90 W, but the real TDP seems to be 60 W.\n",
    "\n",
    "For Threadripper 1950X\n",
    "\n",
    "```sh\n",
    "stress-ng --cpu 0 --cpu-method matrixprod --metrics-brief --rapl --perf -t 60s\n",
    "stress-ng: info:  [135178] setting to a 1 min run per stressor\n",
    "stress-ng: info:  [135178] dispatching hogs: 128 cpu\n",
    "stress-ng: metrc: [135178] stressor       bogo ops real time  usr time  sys time   bogo ops/s     bogo ops/s\n",
    "stress-ng: metrc: [135178]                           (secs)    (secs)    (secs)   (real time) (usr+sys time)\n",
    "stress-ng: metrc: [135178] cpu             1028008     60.02   1908.89      0.59     17128.73         538.37\n",
    "stress-ng: info:  [135178] Cannot read perf counters, do not have CAP_SYS_ADMIN capability or /proc/sys/kernel/perf_event_paranoid is set too high (4)\n",
    "stress-ng: info:  [135178] cpu:\n",
    "stress-ng: info:  [135178]  core                    8.57 W\n",
    "stress-ng: info:  [135178]  pkg-0-die-0           169.95 W\n",
    "stress-ng: info:  [135178]  pkg-0-die-1           169.95 W\n",
    "stress-ng: info:  [135178] skipped: 0\n",
    "stress-ng: info:  [135178] passed: 128: cpu (128)\n",
    "stress-ng: info:  [135178] failed: 0\n",
    "stress-ng: info:  [135178] metrics untrustworthy: 0\n",
    "stress-ng: info:  [135178] successful run completed in 1 min\n",
    "```\n",
    "\n",
    "Intel(R) Xeon(R) CPU E3-1240 V2 @ 3.40GHz\n",
    "\n",
    "```sh\n",
    "$ stress-ng --cpu 0 --cpu-method matrixprod --metrics-brief --rapl --perf -t 60s\n",
    "stress-ng: info:  [5175] setting to a 1 min run per stressor\n",
    "stress-ng: info:  [5175] dispatching hogs: 8 cpu\n",
    "stress-ng: metrc: [5175] stressor       bogo ops real time  usr time  sys time   bogo ops/s     bogo ops/s\n",
    "stress-ng: metrc: [5175]                           (secs)    (secs)    (secs)   (real time) (usr+sys time)\n",
    "stress-ng: metrc: [5175] cpu              342094     60.00    475.41      0.94      5701.11         718.15\n",
    "stress-ng: info:  [5175] Cannot read perf counters, do not have CAP_SYS_ADMIN capability or /proc/sys/kernel/perf_event_paranoid is set too high (4)\n",
    "stress-ng: info:  [5175] cpu:\n",
    "stress-ng: info:  [5175]  core                   40.44 W\n",
    "stress-ng: info:  [5175]  pkg-0                  44.00 W\n",
    "stress-ng: info:  [5175] skipped: 0\n",
    "stress-ng: info:  [5175] passed: 8: cpu (8)\n",
    "stress-ng: info:  [5175] failed: 0\n",
    "stress-ng: info:  [5175] metrics untrustworthy: 0\n",
    "stress-ng: info:  [5175] successful run completed in 1 min\n",
    "```\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "codecarbon",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
